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Unstructured P2P systems exhibit a great deal of robustness and self-healing at the cost of reduced scalability. Resource location is performed using a broadcast-like process called flooding. The work presented in this paper comprises an effort to reduce the overwhelming volume of traffic generated by flooding, thus increasing the scalability of unstructured P2P systems. Using a simple hash-based content categorization method the Ultrapeer overlay network is partitioned into a relatively small number of distinct subnetworks. By employing a novel index splitting technique each leaf peer is effectively connected to each different subnetwork. The search space of each individual flooding is restricted to a single partition, and is thus considerably limited. This reduces significantly the volume of traffic produced by flooding without affecting at all the accuracy of the search method. Experimental results demonstrate the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Achievements in European Research on Grid Systems is the property of Springer eBooks and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Interactive Problem Solving Environments (PSEs) offer an integrated approach for constructing and running complex systems, such as distributed simulation systems. To achieve efficient execution of High Level Architecture (HLA)-based distributed interactive simulations on the Grid, we introduce a PSE called Grid HLA Management System (G-HLAM) for their management. This is done by introducing migration and monitoring mechanisms for such applications. In this paper we present how G-HLAM can be applied to the applications supporting surgeons with simulations of vascular reconstruction, using distributed federations on the Grid for the communication among simulation and visualization components. [ABSTRACT FROM AUTHOR]

Enabling high-level programming models on grids is today a major challenge. A way to achieve this goal relies on the use of environments able to transparently and automatically provide adequate support for low-level, grid-specific issues (fault-tolerance, scalability, etc.). This paper discusses the above approach when applied to grid data management. As a case study, we propose a 2-tier software architecture that supports transparent, fault-tolerant, grid-level data sharing in the ASSIST programming environment (University of Pisa), based on the JuxMem grid data sharing service (INRIA Rennes). [ABSTRACT FROM AUTHOR]

Currently, Grid applications are usually developed for a network offering only a best effort packet delivery service. Nevertheless, High Performance Computing applications with Quality of Service requirements stress the capabilities of the interconnecting network of the target Grid infrastructure. Therefore, the application runtime environment must interact, through a Grid Resource Broker, with a Network Resource Manager to obtain information about the network and to reserve network resources among the computational resources that will host the execution of the applications. The paper presents the design and the development of a Grid Network-Aware Resource Broker. It enhances the features of a Grid Resource Broker with the capabilities provided by a Network Resource Manager. The innovative contribution of the presented integration is the possibility to design and implement new mapping/scheduling mechanisms to take into account both network and computational resources. Finally, we will show how to exploit the new features offered by the Grid Network-Aware Resource Broker in scheduling parallel applications with QoS requirements. [ABSTRACT FROM AUTHOR]

Building and evolving grid applications is complex. A promising approach to managing this complexity is component-based development, currently attracting growing interest in the grid community. Evaluating the effectiveness of component-based development requires real-world experience. To this end, this paper presents a case study in reengineering a high performance numerical solver to become a component-based grid application. The adopted component model is an extension of the generic Fractal model that specifically targets grid environments. The paper provides qualitative and quantitative evidence that componentisation has improved the modifiability and reusability of the application without significantly affecting performance. [ABSTRACT FROM AUTHOR]

As Grids enlarge their boundaries and users, some of their functions should be decentralized to avoid bottlenecks and guarantee scalability. A way to provide Grid scalability is to adopt Peer-to-Peer (P2P) models to implement non hierarchical decentralized Grid services and systems. A core Grid functionality that can be effectively redesigned using the P2P approach is resource discovery. This paper proposes a P2P resource discovery architecture aiming to manage various Grid resources and complex queries. Its goal is two-fold: to address discovery of multiple resources, and to support discovery of dynamic resources and arbitrary queries in Grids. The architecture includes a scalable technique for locating dynamic resources in large-scale Grids. Simulation results are provided to demonstrate the efficiency of the proposed technique. [ABSTRACT FROM AUTHOR]

One way to ease the development of Grid applications is to specify and design an Integrated Toolkit which will enable the development of Grid-unaware applications i.e. applications where the Grid is transparent to them but that are able to exploit its resources. Achieving this vision of an Integrated Toolkit requires the investigation and definition of integration between different systems. This paper studies the integration possibilities of GriCoL, a language for the description of complex Grid experiments, and GRID superscalar, a run-time environment which automatically converts sequential program code and deploys it for execution on a Grid. GriCoL operates on a multi-layer paradigm, using both a control flow layer and a data flow layer. We propose integration with GRID superscalar at each of these layers, concluded that integration at the control flow level is difficult to achieve but at the data flow level is possible. [ABSTRACT FROM AUTHOR]

The emerging Grid applications require rigorous approaches to handle security management issues as their scale, heterogeneity, and complexity can not be handled with simple examination and monitoring mechanisms. In this paper, we propose a rigorous method of deriving security policies for grid applications. These policies are derived from a security requirements model built using the KAOS requirements engineering methodology. We consider an example grid application of distributed file system; its formal security requirements model is developed followed by its refinement and then the derivation of security policy for this application. The derived policies are refined and transformed into operational policies for their implementation. We developed templates for the security policies to facilitate and formalise the various stages of policy derivation. [ABSTRACT FROM AUTHOR]

Interactive problem solving environments are gaining widespread acceptance within the Grid community. While developing applications and frameworks to support and to integrate with these interactive environments is very important, it is also necessary to treat the legacy applications with the same importance. In this paper, we report an ongoing effort in enabling a legacy application to support, integrate with, and evolve as a scalable problem solving environment for Earth system modelling. Our strategy has been to componentise the existing legacy framework, augment each component with metadata, and using this metadata address different issues arising when performing component composition. We describe the means for specifying, publishing, and using the metadata in solving two different but crucially important issues when performing component composition - model validation and model efficiency. [ABSTRACT FROM AUTHOR]

In this paper the use of a Grid-enabled system for performance monitoring of GRID superscalar-compliant applications is addressed. Performance monitoring is built on top of the OCM-G monitoring system developed in the EU IST CrossGrid project. A graphical user tool G-PM is used to interpret information received from the monitoring system. We discuss the issues related to the performance analysis of GRID superscalar applications and present the current work progress with focus on the refinement of existing implementation issues and present the required changes to the G-PM and OCM-G architecture. At the end a case study of performance monitoring is presented. [ABSTRACT FROM AUTHOR]

In SOA-based Grid environments service provider and service consumer usually do not know each other. In order to establish a business relation they must inter alia (i) create a trust relationship, and (ii) set up mechanisms to create reliable, verifiable, and, at least in a commercial environment, also audible agreements with respect to the services requested, delivered and consumed. In this paper we will only briefly address (i) but concentrate on solutions for (ii) based on Service Level Agreements (SLAs). Therefore we will give an overview on the state-of-the-art of SLA usage in Grids, highlight possible obstacles for the deployment of SLAs, and present a detailed example of a service improving the execution of workflows through the use of WS-Agreement to negotiate advance reservation of resources to execute workflow components. [ABSTRACT FROM AUTHOR]

Copyright of Achievements in European Research on Grid Systems is the property of Springer eBooks and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The 2006 MACE workshop [1, 28] has presented the drivers and challenges of Autonomic Networking [2] and fostered an understanding of emerging principles for this new type of networks [3]. In this paper, we present concepts and principles that define a technological neutral, architectural perspective of Autonomic Networks. The work presented in largely based on work within the Architecture team of the TeleManagement Forum (Technological Neutral Architecture, [4]) and joined research work of industrial and academic research teams (for example Ericsson [5], HP & QinetiQ [6] and Motorola [7]). The goal of this paper is to provide the reader with manageability guidelines and architectural patterns leading to the development of manageable autonomic software and communication systems. We present a component-based, distributed system architecture and an associated set of critical system services that Autonomic Networks require. Since we tackle the problem from a technologically neutral angle, this paper will not prescribe a single new technology, but rather provide a means that allows for federating different technologies, each of which offers particular advantages at business and system levels. In particular, it enables business concepts and principles to drive system design and architectures. This may be further implemented using currently available distributed systems information technologies. [ABSTRACT FROM AUTHOR]

"The next thing in technology is not just big but truly huge: the conquest of complexity", Andreas Kluth, The Economist [7]. The future of the Information Society draws a world where devices with processing capabilities are ubiquously connected to information sources. Due to the diversity of user devices, technologies, communication accesses, etc. operators do really need a technology able to manage such a complex environment giving a service end to end vision. In this sense, the set of technologies that arise from Autonomic Communication appears to be the cornerstone in order to manage the complexity of these new networks and services infrastructure. Competitive market is hard and telecommunication operators must face a double challenge, on one hand they must offer powerful services that must be managed, on the other hand they must address the reduction of service margins. Only really efficient operators will survive in such an environment. The I2OSS (Intelligence to Operational Support Systems) model is thought to provide operators with management infrastructures showing the advantages of Autonomic Communications. The reader will find in this article a technological framework for innovation in the field of Autonomic Communications. The I2OSS model establishes a methodological approach for innovation on OSS (Operation Support Systems) systems that support the management processes of a telco operator. No concrete or specific solutions will be found, but indications on how a telco operator must drive innovation to take advantage of "Autonomic Technologies". [ABSTRACT FROM AUTHOR]

Current network management systems have been impeded by a scarcity of open standards for interoperable management solutions. Information models have made progress in promoting interoperability of traditional "centralised" networks but have still to significantly address the proliferation of next generation networks such as autonomic networks. Such networks impose challenges which include distributed self-control and self-management. The goal of the Madeira project was to utilise novel technologies and methodologies, based on an underlying P2P paradigm, for a logically meshed, distributed Network Management System (NMS) that facilitates dynamic behaviour of transient network elements. In this paper, we describe a solution for a meta-model that attempts to capture the key concepts behind the task of network management of a mesh network. A case-study focusing on the fault management of such a network will be presented with the purpose of verifying the applicability of such a meta-model. [ABSTRACT FROM AUTHOR]

This paper presents an approach to manipulating available hybrid connectivity to autonomically maximise the potential for sustained connectivity in the event of path disruptions. The approach is documented in terms of the features, architecture and deployment modes of an autonomic communications module, termed RASCAL. This module employs software-agent logic supported by a state-of-the-art policy engine to dynamically determine best options for packet transmission over available infrastructure and ad-hoc connections. [ABSTRACT FROM AUTHOR]

During the last decade, networks have been growing dramatically on several dimensions: the number of users has been multiplied by more than 15, the amount of traffic by more than 100 and the number of network technologies and usages has also been diversified. One of the main consequences of this growth is the increase in dynamicity of the network behaviour. Therefore, it is more and more difficult for human operators to manage the network in an efficient way. That is why current research in the field of network management tends to automate network control and management. A large initiative has been proposed by IBM to give more autonomy to computing systems: Autonomic Computing Initiative. The paradigm of Autonomic Networking was introduced as an extension of Autonomic Computing, focusing on the autonomy of networks. At the centre of it lies knowledge management. In fact, to be self-managed, a network element needs to know a lot about its environment. But sharing a large amount of knowledge over a large network is very expensive in terms of resources. Therefore, new knowledge management mechanisms are required. A good example of networks that need to be autonomic is military networks. In fact, on one hand, military communication environment is very dynamic, and very uncertain; and on the other hand, quick decisions have to be triggered to guarantee -whenever it is possible- the connectivity for strategical communications. This paper proposes an interpretation of the Autonomic Networking paradigm, a description of a situatedness-based knowledge plane, and an instantiation of these concepts to a concrete application: resource regulation in IP military networks. [ABSTRACT FROM AUTHOR]

This chapter presents the Living Systems Autonomic Service Access Management Suite, LS/ASAM, a comprehensive middleware solution enabling adaptive connectivity management of nomadic end hosts across heterogeneous access networks with autonomic optimisation of network performance and availability. [ABSTRACT FROM AUTHOR]

Autonomic communication aims to build more reflective systems with properties like self-healing, self-organisation, self-optimisation and so forth — the so-called "self-*" properties. To attain this within the existing strictly-layered approaches to network software may be possible to certain extent, but will not leverage all the possible optimisations, and we suggest that cross-layer architectures are better-suited to achieving the self-* properties. This paper explores the possibilities of cross-layering approaches in autonomic networks, reviews and compares the different cross-layer approaches to network architecture, observing that most current approaches depend purely on local information and provide only poor and inaccurate information gathering at the network level. [ABSTRACT FROM AUTHOR]

MPLS DiffServ-TE combines the advantages of DiffServ and MPLSTE by allowing a differentiation of services and a traffic engineering based on a fast packet switching technology. However, such MPLS DiffServ-TE network needs an efficient method for Quality of Service (QoS) guaranteeing. In addition, the management of such a network is not a simple function and could not be done manually. In fact, it would be much more economic and effective to let equipments handle a part of the tasks attributed currently to the human administrator. In this paper, a novel architecture based on a Multi-Agent System is proposed to automatically manage MPLS DiffServ-TE domains. To meet the QoS requirements, an LSP creation strategy, based on a traffic-driven approach and depending on the traffic load, is proposed. It determines when to set up a new LSP and when to forward a new traffic in an already existing one. This strategy reduces the number of LSPs and the number of signalling operations in the network. Simulation results are provided to illustrate the efficiency of our proposition. [ABSTRACT FROM AUTHOR]

In order to enable the autonomic network resource management, we resort to game theory to facilitate the spectrum sharing between heterogeneous wireless networks. We set the spectrum sharing objective to improve spectrum efficiency and maximise network revenue. Based on this goal, we propose a revenue sharing bargain game to model the spectrum sharing behaviour of intra-operator radio access networks (RANs) and a price bargain game to model the spectrum trading behaviour between inter-operator RANs. Furthermore, we adopt multi-agent architecture to implement the spectrum sharing schemes autonomously. Both bargaining mechanisms are analysed using bargaining game theory, and consequently the implementations are refined and simplified based on the analysis. Simulation results show that the proposed mechanisms outperform the conventional fixed spectrum management method in network revenue, spectrum efficiency and call blocking rate. [ABSTRACT FROM AUTHOR]

An enormous amount of multimedia data will be transmitted by various devices in the wireless personal area network, and this network environment will require very high transmission capacity. In this paper, we apply multiple antennas to MB-OFDM UWB system for high performance. With an emphasis on a preamble design for multichannel separation, we address the channel estimation in MB-OFDM system with multiple antennas. By properly designing each preamble for multiple antennas to be orthogonal in the time domain, the channel estimation can be applied to the MB-OFDM proposal for IEEE 802.15.3a standard in the case of more than two transmit antennas. By using the multiantenna scheme and proposed channel estimation technique, the reliability and performance of the MB-OFDM system can be improved. [ABSTRACT FROM AUTHOR]

A combination of OFDM with FDMA (called OFDMA) is regarded as a promising solution for improving the performance of BWA with multiple users. Although transmit diversity is clearly advantageous in OFDMA systems, it may not be possible that practical OFDMA systems have more than two antennas due to size, cost, or hardware limitations. Cooperative networks aim to utilize the available terminals as a collection of distributed antennas for the transmission of signals from one end of the network to the other. This paper focuses on design and performance evaluation of IEEE 802.16 MIMO-OFDMA systems with cooperative diversity. In this chapter, for high-rate and reliable transmission, efficient transmission codes of cooperative transmission are proposed for each transmission case (single transmission case or mutual transmission case). [ABSTRACT FROM AUTHOR]

Radio frequency identification (RFID) technology is not fundamentally new and concerns a whole range of applications. The first RFID application may have been the Royal British Air Force's "Identify Friend or Foe" system, which was used during the Second World War to identify friendly aircraft. RFID can be applied to a variety of tasks, structures, work systems, and contexts along the value chain, including business-to-business (B-2-B) logistics, internal operations, business-toconsumer (B-2-C) marketing, and after-sales service applications [1-6]. However, the boom that RFID technology enjoys today is basically due to the standardization [7] and development of low cost devices. Like every wireless device, RFID systems bring with them security and privacy issues to all those people who have been working in this area. Security issues involve classic attacks, namely denial of service, impersonation of tags, or channel eavesdropping. These attacks are rendered more practicable because of the tags' lack of computational and storage capacity. There are many papers investigating these issues in various ways [7, 8, 10-12, 14]. Today's challenge is to find protocols (or deployments) which allow authorized parties to identify the tags without an adversary being able to track them, thus getting to the root of the privacy problem [8, 13]. It is well known that the reason not to use well known authentication protocols is that such protocols do not preserve the privacy of the provider. Asymmetric cryptography could easily solve this problem, but it is too heavy to be implemented within a tag. [ABSTRACT FROM AUTHOR]

Searching information on the Web can be viewed as extremely easy, or it can be extremely difficult. This is because the WWW is not indexed like many library catalogs or journal-article indexes. When we search on the Web, we are not searching it directly but are actually searching the Web pages collected and indexed by a search tool from computers all over the world that contains the actual Web pages. Examples of search tools are Yahoo! Search, Google, Alta Vista, and so on. The different types of search tools have their own strengths and weaknesses. Depending on your information needs, one may work better for you than another. Search directories are hierarchical databases with references to websites. The websites that are included are classified according to the rules of that particular search service. Search engines, on the other hand, use software to crawl the Internet in search of what you would like using of terms or keywords. Specialized databases are the hidden parts of the WWW that are normally not found by regular search engines [1]. This paper presents the extension work from Integrated Filtered Web-Search Engine (IFWSE) [2] by looking at the enhancement of the program structure to retrieve the search hits. Further experiments were also carried out to compare its performance with with a well-established, meta-search engine-the MetaCrawler [3] [4]. [ABSTRACT FROM AUTHOR]

Tamper-resistant software which implements a block cipher with a fixed embedded cryptographic key is important for securing embedded systems for digital rights management, access control, and other applications. The security of such software is measured by its ability to hide the embedded key against numerous known attacks. A class of methods for constructing tamper-resistant software by using a number of look-up tables is called a white-box implementation or table-network implementation. We developed a method of evaluating the security of table-network implementations of the Data Encryption Standard (DES). Link and Neumann proposed a table-network implementation of DES that is claimed to be resistant against all known attacks, which are effective for table-network implementations of DES proposed by Chow, Eisen, Johnson, and van Oorschot. In this paper, we point out the existence of a new attack, which allows efficient extraction of the hidden key in the Link-Newman table-network implementation of DES. Our result should contribute in completing the list of attacking methodologies and thus help the design of better tamper-resistant software. [ABSTRACT FROM AUTHOR]

In the recent years, several practical methods have been published to compute collisions on some commonly used hash functions. Starting from two messages m1 and m2 these methods permit to compute m1′ and m2′ similar to the former such that they have the same image for a given hash function. In this paper we present a method to take into account, at the symbolic level, that an intruder actively attacking a protocol execution may use these collision algorithms in reasonable time during the attack. This decision procedure relies on the reduction of constraint solving for an intruder exploiting the collision properties of hash functions to constraint solving for an intruder operating on words, that is with an associative symbol of concatenation. The decidability of the latter is interesting in its own right as it is the first decidability result that we are aware of for an intruder system for which unification is infinitary, and permits to consider in other contexts an associative concatenation of messages instead of their pairing. [ABSTRACT FROM AUTHOR]

Web Services have become more and more important in these years, and BPEL4WS is a de facto standard for the web service composition and orchestration. We have proposed a language BPEL0 to capture the important features of BPEL4WS, with the scope-based compensation and fault handling mechanism. In this paper we formalize the denotational semantics for BPEL0, which can support the refinement calculus and the verification of program equivalence. A set of algebraic laws is investigated within the denotational framework. The distinct features of BPEL0 make the investigation of the denotational semantics and algebraic laws more challenging. [ABSTRACT FROM AUTHOR]

In their seminal paper on certificateless public key cryptography, Al-Riyami and Paterson (AP) proposed a certificateless authenticated key agreement protocol. Key agreement protocols are one of the fundamental primitives of cryptography, and allow users to establish session keys securely in the presence of an active adversary. AP's protocol essentially requires each party to compute four bilinear pairings. Such operations can be computationally expensive, and should therefore be used moderately in key agreement. In this paper, we propose a new certificateless authenticated two-party key agreement protocol that only requires each party to compute two pairings. We analyze the security of the protocol and show that it achieves the desired security attributes. Furthermore, we show that our protocol can be used to establish keys between users of different key generation centers. [ABSTRACT FROM AUTHOR]

Digital Rights Management frameworks (DRM) aim at protecting and controlling information contents widely distributed on client devices. Using a license, the content provider can decide which rights can be rendered and who are the authorized end-users (as identity holders) allowed to exercise those rights. Most of the time, it is hard to add new feature to the client application, it is even impossible when the new feature is not considered trustworthy by the corporation distributing the rendering application. In a same way, the rendering application identifies the end-user with a dedicated identity and it is impossible to take into account an identity provided by an external corporation. In this paper, we aim at providing a federated approach called FORM where a content provider can decide to trust external rendering rights and external identities. We even go further introducing identity providers, actions providers as we consider content providers. Thus, all kind of providers can define license specifying what can be done with the object they provide. FORM defines a new license model and a new license interpretation mechanism taking into account all licenses issued by a federation of object providers. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel method of safety analysis for runtime code update, i.e., updating a program at runtime without terminating its execution. Runtime code update is an emerging technique especially for increasing availability of the servers which should always be in service and free of any known bugs or security flaws. However, it may cause state inconsistency or unintended behaviors unless it is properly restricted. Although too much restriction enables us to easily ensure safety of updating code at runtime, it prevents us from coping with the realistic updates. To reveal appropriate restriction, we first construct a very precise model of safe runtime code update based on a framework of explicit data/control flow and dependency. Then, a class of analyses which statically estimates the set of safe update points is derived by approximating the model. We restrict only the timing: behaviorally safe runtime code update may occur only at safe update points. Moreover, we can relax the restriction by explicitly specifying non-critical points. [ABSTRACT FROM AUTHOR]

Non-interference is typically used as a baseline security policy to formalize confidentiality of secret information manipulated by a program. In contrast to static checking of non-interference, this paper considers dynamic, automaton-based, monitoring of information flow for a single execution of a sequential program. The monitoring mechanism is based on a combination of dynamic and static analyses. During program execution, abstractions of program events are sent to the automaton, which uses the abstractions to track information flows and to control the execution by forbidding or editing dangerous actions. The mechanism proposed is proved to be sound, to preserve executions of well-typed programs (in the security type system of Volpano, Smith and Irvine), and to preserve some safe executions of ill-typed programs. [ABSTRACT FROM AUTHOR]

Control-hijacking attacks are known as critical threats to software security. Control flow monitoring is a kind of important method to mitigate this problem. In this paper, we present a new method for program control flow monitoring. Based on the static analysis of a program, we apply very simple instrumentation of a program's source code to encode its runtime function level control flow traces and check the correctness of the traces in the OS kernel. Experiments show that this method has a tiny performance impact and is still highly effective in detecting control-hijacking attacks. We also propose to automatically handle non-standard control flow by learning programs' dynamic profiling data. Our method is hopeful to be enforceable in different environments because it does not depend closely on specific platform features and the underlying techniques can be easily found in many platforms. [ABSTRACT FROM AUTHOR]

We present modular formalizations of the model specification language Reactive Modules and the temporal logic CTL* in the proof assistant Coq. In our formalizations, both shallow and deep embeddings of each language are given. The modularity of our formalizations allows proofs and theorems to be reused across different embeddings. We illustrate the advantages of our modular formalizations by proving the mutual exclusion property of the Bakery algorithm in different embeddings. [ABSTRACT FROM AUTHOR]

A major difficulty for tracking information flow in multithreaded programs is due to the internal timing covert channel. Information is leaked via this channel when secrets affect the timing behavior of a thread, which, via the scheduler, affects the interleaving of assignments to public variables. This channel is particularly dangerous because, in contrast to external timing, the attacker does not need to observe the actual execution time. This paper presents a compositional transformation that closes the internal timing channel for multithreaded programs (or rejects the program if there are symptoms of other flows). The transformation is based on spawning dedicated threads, whenever computation may affect secrets, and carefully synchronizing them. The target language features semaphores, which have not been previously considered in the context of termination-insensitive security. [ABSTRACT FROM AUTHOR]

In a process calculus, an agent guarantees responsive usage of a channel name r if a communication along r is guaranteed to eventually take place. Responsiveness is important, for instance, to ensure that any request to a service be eventually replied. We propose two distinct type systems, each of which statically guarantees responsive usage of names in well-typed pi-calculus processes. In the first system, we achieve responsiveness by combining techniques for deadlock and livelock avoidance with linearity and receptiveness. The latter is a guarantee that a name is ready to receive as soon as it is created. These conditions imply relevant limitations on the nesting of actions and on multiple use of names in processes. In the second system, we relax these requirements so as to permit certain forms of nested inputs and multiple outputs. [ABSTRACT FROM AUTHOR]

Given an arbitrary intruder deduction capability, modeled as an inference system ${\cal S}$ and a protocol, we show how to compute an inference system $\widehat{\cal S}$ such that the security problem for an unbounded number of sessions is equivalent to the deducibility of some message in $\widehat{\cal S}$. Then, assuming that $\cal S$ has some subformula property, we lift such a property to $\widehat{S}$, thanks to a proof normalisation theorem. In general, for an unbounded number of sessions, this provides with a complete deduction strategy. In case of a bounded number of sessions, our theorem implies that the security problem is co-NP-complete. As an instance of our result we get a decision algorithm for the theory of blind-signatures, which, to our knowledge, was not known before. [ABSTRACT FROM AUTHOR]

We report on a man-in-the-middle attack on PKINIT, the public key extension of the widely deployed Kerberos 5 authentication protocol. This flaw allows an attacker to impersonate Kerberos administrative principals (KDC) and end-servers to a client, hence breaching the authentication guarantees of Kerberos. It also gives the attacker the keys that the KDC would normally generate to encrypt the service requests of this client, hence defeating confidentiality as well. The discovery of this attack caused the IETF to change the specification of PKINIT and Microsoft to release a security update for some Windows operating systems. We discovered this attack as part of an ongoing formal analysis of the Kerberos protocol suite, and we have formally verified several possible fixes to PKINIT—including the one adopted by the IETF—that prevent our attack. [ABSTRACT FROM AUTHOR]

In the investigation of the relationship between the formal and the computational view of cryptography, a recent approach, first proposed in [10], uses static equivalence from cryptographic pi calculi as a notion of formal indistinguishability. Previous work [10,1] has shown that this yields the soundness of natural interpretations of some interesting equational theories, such as certain cryptographic operations and a theory of XOR. In this paper however, we argue that static equivalence is too coarse to allow sound interpretations of many natural and useful equational theories. We illustrate this with several explicit examples in which static equivalence fails to work. To fix the problem, we propose a notion of formal indistinguishability that is more flexible than static equivalence. We provide a general framework along with general theorems, and then discuss how this new notion works for the explicit examples where static equivalence fails to ensure soundness. [ABSTRACT FROM AUTHOR]

Extending a compositional protocol logic with an induction rule for secrecy, we prove soundness for a conventional symbolic protocol execution model, adapt and extend previous composition theorems, and illustrate the logic by proving properties of two key agreement protocols. The first example is a variant of the Needham-Schroeder protocol that illustrates the ability to reason about temporary secrets. The second example is Kerberos V5. The modular nature of the secrecy and authentication proofs for Kerberos makes it possible to reuse proofs about the basic version of the protocol for the PKINIT version that uses public-key infrastructure instead of shared secret keys in the initial steps. [ABSTRACT FROM AUTHOR]

A type-theoretic framework for formal reasoning with different logical foundations is introduced and studied. With logic-enriched type theories formulated in a logical framework, it allows various logical systems such as classical logic as well as intuitionistic logic to be used effectively alongside inductive data types and type universes. This provides an adequate basis for wider applications of type theory based theorem proving technology. Two notions of set are introduced in the framework and used in two case studies of classical reasoning: a predicative one in the formalisation of Weyl's predicative mathematics and an impredicative one in the verification of security protocols. [ABSTRACT FROM AUTHOR]

Software security can be ensured by specifying and verifying security properties of software using formal methods with strong theoretical bases. In particular, programs can be modeled in the framework of lambda-calculi, and interesting properties can be expressed formally by contextual equivalence (a.k.a. observational equivalence). Furthermore, imperative features, which exist in most real-life software, can be nicely expressed in the so-called computational lambda-calculus. Contextual equivalence is difficult to prove directly, but we can often use logical relations as a tool to establish it in lambda-calculi. We have already defined logical relations for the computational lambda-calculus in previous work. We devote this paper to the study of their completeness w.r.t. contextual equivalence in the computational lambda-calculus. [ABSTRACT FROM AUTHOR]

In this paper, we present a spatial logic for higher order π-calculus. In order to prove that the induced logical equivalence coincides with context bisimulation, we present some new bisimulations, and prove the equivalence between these new bisimulations and context bisimulation. Furthermore, we present a variant of this spatial logic and prove that it also provides a logical characterisation of context bisimulation. [ABSTRACT FROM AUTHOR]

We aim to provide information hiding support in concurrent object-oriented programming languages. We study this issue both at the object level and the class level, in the context of an object-oriented extension of Join — a process calculus in the tradition of the π-calculus. In this extended abstract, we focus on the class level and design a new hiding operation on classes. The purpose of this operation is to prevent part of parent classes from being visible in client (inheriting) classes. We define its formal semantics in terms of α-converting hidden names to fresh names, and its typing in terms of eliminating hidden names from class types. [ABSTRACT FROM AUTHOR]

A component-based realtime system is a simple model for the server-client relation with time constraints. This paper presents an efficient algorithm, called a blackbox testing algorithm, for detecting the emptiness of a component-based realtime system. This algorithm was originally proposed in [5], but with a certain flaw. We improve it and correct the flaw by using urgency [2] of transitions. [ABSTRACT FROM AUTHOR]

XML document is a very popular way to transfer data between databases because of its simplicity of structure and text based data storage. In some typical implementation scenarios where XML document is used to transfer data as XML database, it is necessary to check the consistency of the data at destination. If users are responsible for storing and transferring the document, there is a possibility of data manipulation. In this paper, we propose to apply data verification techniques including checksum and hash algorithms for data verification of XML document. As an advantage, we show that we not only can check the document's authenticity, but also we can identify the specific modified portions of the document. We discuss many popular checksum techniques and secured hash algorithms applied to XML document and compare their efficiency on data verification in the scenarios of the XML data transfer. [ABSTRACT FROM AUTHOR]

The program dependence graph (PDG) represents data and control dependences between statements in a program. The PDG is a useful intermediate representation for compiler code optimizations, because compiler code optimizations mostly rely on data and control dependence information. However, the validity of optimization methods based on PDGs has not been well studied. In order to justify optimization based on PDGs, it is necessary to introduce a formal semantics of PDGs. This paper presents an operational semantics of PDGs corresponding to programs which have an unstructured control flow. Our PDG semantics is equivalent to sequential program semantics in the sense that a CFG and the corresponding PDG perform the same computation. [ABSTRACT FROM AUTHOR]

We describe the structure of the abstract domains in the Astrée static analyzer, their modular organization into a hierarchical network, their cooperation to over-approximate the conjunction/reduced product of different abstractions and to ensure termination using collaborative widenings and narrowings. This separation of the abstraction into a combination of cooperative abstract domains makes Astrée extensible, an essential feature to cope with false alarms and ultimately provide sound formal verification of the absence of runtime errors in very large software. [ABSTRACT FROM AUTHOR]

Tse and Zdancewic have formalized the notion of noninterference for Abadi et al.'s DCC in terms of logical relations and given a proof by reduction to parametricity of System F. Unfortunately, their proof contains errors in a key lemma that their translation from DCC to System F preserves the logical relations defined for both calculi. We prove noninterference for a variant of DCC by reduction to the basic lemma of a logical relation for the simply typed λ-calculus, using a fully complete translation to the simply typed λ-calculus. Full completeness plays an important role in showing preservation of the two logical relations through the translation. [ABSTRACT FROM AUTHOR]

A modular formalization of the branching time temporal logic CTL* is presented. Our formalization subsumes prior formalizations of propositional linear temporal logic (PTL) and computation tree logic (CTL). Moreover, the modularity allows to instantiate our formalization for different formal security models. Validity of axioms and soundness of inference rules in axiomatizations of PTL, UB, CTL, and CTL* are discussed as well. [ABSTRACT FROM AUTHOR]

Polyhedral analysis [9] is an abstract interpretation used for automatic discovery of invariant linear inequalities among numerical variables of a program. Convexity of this abstract domain allows efficient analysis but also loses precision via convex-hull and widening operators. To selectively recover the loss of precision, sets of polyhedra (disjunctive elements) may be used to capture more precise invariants. However a balance must be struck between precision and cost. We introduce the notion of affinity to characterize how closely related is a pair of polyhedra. Finding related elements in the polyhedron (base) domain allows the formulation of precise hull and widening operators lifted to the disjunctive (powerset extension of the) polyhedron domain. We have implemented a modular static analyzer based on the disjunctive polyhedral analysis where the relational domain and the proposed operators can progressively enhance precision at a reasonable cost. [ABSTRACT FROM AUTHOR]

It is customary to write performance-critical parts of arithmetic functions in assembly: this enables finely-tuned algorithms that use specialized processor instructions. However, such optimizations make formal verification of arithmetic functions technically challenging, mainly because of many bit-level manipulations of data. In this paper, we propose an approach for formal verification of arithmetic functions in assembly. It consists in the implementation in the Coq proof assistant of (1) a Hoare logic for assembly programs augmented with loops and (2) a certified translator to ready-to-run assembly with jumps. To properly handle formal verification of bit-level manipulations of data, we propose an original encoding of machine integers. For concreteness, we use the SmartMIPS assembly language, an extension of the MIPS instruction set for smartcards, and we explain the formal verification of an optimized implementation of the Montgomery multiplication, a de facto-standard for the implementation of many cryptosystems. [ABSTRACT FROM AUTHOR]

Keyword-based image search engines such as Google Images are now very popular for accessing large amount of images on the Internet. Because only the text information that are directly or indirectly linked to the images are used for image indexing and retrieval, most existing image search engines such as Google Images may return large amount of junk images which are irrelevant to the given queries. To filter out the junk images from Google Images, we have developed a kernel-based image clustering technique to partition the images returned by Google Images into multiple visually-similar clusters. In addition, users are allowed to input their feedbacks for updating the underlying kernels to achieve more accurate characterization of the diversity of visual similarities between the images. To help users assess the goodness of image kernels and the relevance between the returned images, a novel framework is developed to achieve more intuitive visualization of large amount of returned images according to their visual similarity. Experiments on diverse queries on Google Images have shown that our proposed algorithm can filter out the junk images effectively. Online demo is also released for public evaluation at: http://www.cs.uncc.edu/~jfan/google−demo/. [ABSTRACT FROM AUTHOR]

Video is a kind of structured data with multi-layer (ML) information, e.g., a shot is consisted of three layers including shot, key-frame, and region. Moreover, multi-instance (MI) relation is embedded along the consecutive layers. Both the ML structure and MI relation are essential for video concept detection. The previous work [5] dealt with ML structure and MI relation by constructing a MLMI kernel in which each layer is assumed to have equal contribution. However, such equal weighting technique cannot well model MI relation or handle ambiguity propagation problem, i.e., the propagation of uncertainty of sub-layer label through multiple layers, as it has been proved that different layers have different contributions to the kernel. In this paper, we propose a novel algorithm named MILC2 (Multi-Layer Multi-Instance Learning with Inter-layer Consistency Constraint.) to tackle the ambiguity propagation problem, in which an inter-layer consistency constraint is explicitly introduced to measure the disagreement of inter-layers, and thus the MI relation is better modeled. This learning task is formulated in a regularization framework with three components including hyper-bag prediction error, inter-layer inconsistency measure, and classifier complexity. We apply the proposed MILC2 to video concept detection over TRECVID 2005 development corpus, and report better performance than both standard Support Vector Machine based and MLMI kernel methods. [ABSTRACT FROM AUTHOR]

We present a level-set based implicit active contour method which can detect innermost homogeneous regions which are often considered feature regions or lines depending on the width of the regions. The curve evolution algorithm is derived from optimization of energy defined for the evolving curves. The energy has basically three terms: the first is the energy of the regions inside the curves, the second the energy of the bands inside the curves, and the third the energy of the bands outside the curves. If the band width is small, the total energy is minimized when the evolving curves lie at the boundaries of the innermost homogeneous regions, and the regions inside the curves are considered feature regions. Our method contrasts with the Chan-Vese model, which does not have the notion of innermost homogeneous regions but tries to find the curves such that the regions inside and outside them are both homogeneous. Our model approaches Chan-Vese model as the band width is increased, and is equivalent to Chan-Vese model when the band width is sufficiently large, so that all points inside/outside the curves lie within the bands inside/outside the curves, respectively. [ABSTRACT FROM AUTHOR]

In this paper, we have proposed a novel algorithm to achieve automatic multi-level image annotation by incorporating concept ontology and multi-task learning for hierarchical image classifier training. To achieve more reliable image classifier training in high-dimensional heterogeneous feature space, a new algorithm is proposed by incorporating multiple kernels for diverse image similarity characterization, and a multiple kernel learning algorithm is developed to train the SVM classifiers for the atomic image concepts at the first level of the concept ontology. To enable automatic multi-level image annotation, a novel hierarchical boosting algorithm is proposed by incorporating concept ontology and multi-task learning to achieve hierarchical image classifier training. [ABSTRACT FROM AUTHOR]

In this paper we present a novel video text detection and segmentation system. In the detection stage, we utilize edge density feature, pyramid strategy and some weak rules to search for text regions, so that high detection rate can be achieved. Meanwhile, to eliminate the false alarms and improve the precision rate, a multilevel verification strategy is adopted. In the segmentation stage, a precise polarity estimation algorithm is firstly provided. Then, multiple frames containing the same text are integrated to enhance the contrast between text and background. Finally, a novel connected components based binarization algorithm is proposed to improve the recognition rate. Experimental results show the superior performance of the proposed system. [ABSTRACT FROM AUTHOR]

In this paper, we present an adaptive foreground object extraction algorithm for real-time video surveillance, in conjunction with a human detection technique applied in the extracted foreground regions by using AdaBoost learning algorithm and Histograms of Oriented Gradient (HOG) descriptors. Furthermore, a RANSAC-based temporal tracking algorithm is also applied to refine and trace the detected human windows in order to increase the detection accuracy and reduce the false alarm rate. The traditional background subtraction technique usually cannot work well for situations with lighting variations in the scene. The proposed algorithm employs a two-stage foreground/background classification procedure to perform background subtraction and remove the undesirable subtraction results due to shadow, automatic white balance, and sudden illumination change. Experimental results on some real surveillance video are shown to demonstrate the good performance of the proposed adaptive foreground extraction algorithm under a variety of different environments with lighting variations and human detection system. [ABSTRACT FROM AUTHOR]

In applications such as video post-production users are confronted with large amounts of redundant unedited raw material, called rushes. Viewing and organizing this material are crucial but time consuming tasks. Typically multiple but slightly different takes of the same scene can be found in the rushes video. We propose a method for detecting and clustering takes of one scene shot from the same or very similar camera positions. It uses a variant of the LCSS algorithm to find matching subsequences in sequences of visual features extracted from the source video. Hierarchical clustering is used to group the takes of one scene. The approach is evaluated in terms of correctly assigned takes using manually annotated ground truth. [ABSTRACT FROM AUTHOR]

This paper presents an images based 3D model retrieval method in which each model is described by six 2D images. The images are generated by three steps: 1) the model is normalized based on the distribution of the surface normal directions; 2) then, the normalized model is uniformly sampled to generate a number of random points; 3) finally, the random points are projected along six directions to create six images, each of which is described by Zernike moment feature. In the comparison of two models, six images of each model are naturally divided into three pairs, and the similarity between two models is calculated by summing up the distances of all corresponding pairs. The effectiveness of our method is verified by comparative experiments. Meanwhile, high matching speed is achieved, e.g., it takes about 3e-5 seconds to compare two models using a computer with Pentium IV 3.00GHz CPU. [ABSTRACT FROM AUTHOR]

Web image search today is mostly keyword-based and explores the content surrounding the image. Searching for images related to a certain location quickly shows that Web images typically do not reveal their explicit relation to an actual geographic position. The geographic semantics of Web images are either not available at all or hidden somewhere within the the Web pages' content. Our spatial search engine crawls and identifies Web pages with a spatial relationship. Analysing location-related Web pages, we identify photographs based on content-based image analysis as well as image context. Following the photograph classification, a location-relevance classification process evaluates image context and content against the previously identified address. The results of our experiments show that our approach is a viable method for Web image location assessment. Thus, a large number of potentially geographically-related Web images are unlocked for commercially relevant spatial Web image search. [ABSTRACT FROM AUTHOR]

The paper presents a method for fingerprint segmentation, which executes in two phases. The enrolled image is partitioned into block by block and a preliminary segmentation is firstly carried out based on thresholding the blockwise variance. Afterwhich, the segmentation result is refined by energy information, where the blocks with the most "reliable" energy are selected to polish the preliminary result and yield the final segmentation map. Reliability of the method has been demonstrated using NIST and FVC data sets. Comparison with other methods is presented. [ABSTRACT FROM AUTHOR]

Effective similarity search in multi-media time series such as video or audio sequences is important for content-based multi-media retrieval applications. We propose a framework that extracts a sequence of local features from large multi-media time series that reflect the characteristics of the complex structured time series more accurately than global features. In addition, we propose a set of suitable local features that can be derived by our framework. These features are scanned from a time series amplitude-levelwise and are called amplitude-level features. Our experimental evaluation shows that our method models the intuitive similarity of multi-media time series better than existing techniques. [ABSTRACT FROM AUTHOR]

We propose a new method for localizing a sound source in a known space with non-calibrated microphones. Our method does not need the accurate positions of the microphones that are required by traditional sound source localization. Our method can make use of wide variety of microphone layout in a large space because it does not need calibration step on installing microphones. After a number of sampling points have been stored in a database, our system can estimate the nearest sampling point of a sound by utilizing the set of time delays of microphone pairs. We conducted a simulation experiment to determine the best microphone layout in order to maximize the accuracy of the localization. We also conducted a preliminary experiment in real environment and obtained promising results. [ABSTRACT FROM AUTHOR]

Recently, video surveillance has received a lot of attention as a technology to realize a secure and safe community. Video surveillance is useful for crime deterrence and investigations, but may cause the invasion of privacy. In this paper, we propose a video surveillance system named PriSurv, which is characterized by visual abstraction. This system protects the privacy of objects in a video by referring to their privacy policies which are determined according to closeness between objects in the video and viewers monitoring it. A prototype of PriSurv is able to protect the privacy adaptively through visual abstraction. [ABSTRACT FROM AUTHOR]

In modern multimedia databases, objects can be represented by a large variety of feature representations. In order to employ all available information in a best possible way, a joint statement about object similarity must be derived. In this paper, we present a novel technique for multi-represented similarity estimation which is based on probability distributions modeling the connection between the distance value and object similarity. To tune these distribution functions to model the similarity in each representation, we propose a bootstrapping approach maximizing the agreement between the distributions. Thus, we capture the general notion of similarity which is implicitly given by the distance relationships in the available feature representations. Thus, our approach does not need any training examples. In our experimental evaluation, we demonstrate that our new approach offers superior precision and recall compared to standard similarity measures on a real world audio data set. [ABSTRACT FROM AUTHOR]

We present a novel interface of a digital music authoring tool that is designed for children. Our system consists of a unique multimodal input device and corresponding platform to support children's music authoring. By departing from the conventional design approaches of existing tools, our system provides a simple and intuitive environment for young children to use. The proposed interface is tested with children in a focus group study, and the results of the study are encouraging in that the children were able to perform some of complicated multitrack recording tasks within a single session that lasted for 15 to 20 minutes. [ABSTRACT FROM AUTHOR]

With the explosive growth of multimedia data, video presentation has become an important technology for fast browsing of video content. In this paper, we present a novel video presentation technique called "Free-Shaped Video Collage" (FS-Collage), which is motivated from and built upon our previous work on Video Collage [3]. Video Collage is a kind of static summary which selects the most representative regions-of-interest (ROI) from video and seamlessly arranges them on a synthesized image. Unlike Video Collage in which both the shapes of ROI and final collage are fixed as rectangle, we support arbitrary shapes of ROI and a set of collage templates in FS-Collage. Furthermore, we design three ROI arrangement schemes (i.e., book, diagonal, and spiral) for satisfying different video genres. We formulate the generation of FS-Collage as an energy minimization problem and solve the problem by designing a random sampling process. The experiment results show that our FS-Collage achieves satisfying performance. [ABSTRACT FROM AUTHOR]

In this paper, we propose an automatic home video skimming system based on media aesthetics. Unlike other similar works, the proposed system considers video editing theory and realizes the idea of computational media aesthetics. Given a home video and a incidental background music, this system generates a music video (MV) style skimming video automatically, with consideration of video quality, music tempo, and the editing theory. The background music is analyzed so that visual rhythm caused by shot changes in the skimming video are synchronous with the music tempo. Our work focuses on the rhythm over aesthetic features, which is more recognizable and more suitable to describe the relationship between video and audio. Experiments show that the generated skimming video is effective in representing the original input video, and the audio-video conformity is satisfactory. [ABSTRACT FROM AUTHOR]

The increasing popularity of music recommendation systems and the recent growth of online music communities further emphasizes the need for effective playlist management tools able to create, share, and personalize playlists. This paper proposes the development of generic playlists and presents a concrete scenario to illustrate their possibilities. Additionally, to enable the development of playlist management tools, a formal foundation is provided. Therefore, the concept of fuzzy lists is defined and a corresponding algebra is developed. Fuzzy lists offer a solution perfectly suited to meet the demands of playlist management. [ABSTRACT FROM AUTHOR]

Recently, there are so many videos available for people to choose to watch. To solve this problem, we propose a tagging system for video content based on facial expression that can be used for recommendations based on video content. Viewer's face captured by a camera is extracted by Elastic Bunch Graph Matching, and the facial expression is recognized by Support Vector Machines. The facial expression is classified into Neutral, Positive, Negative and Rejective. Recognition results are recorded as "facial expression tags" in synchronization with video content. Experimental results achieved an averaged recall rate of 87.61%, and averaged precision rate of 88.03%. [ABSTRACT FROM AUTHOR]

The ubiquity of camera phones provides a convenient platform to develop immersive mixed-reality games. In this paper we introduce such a game which is loosely based on the popular card game "Memory", where players are asked to match a pair of identical cards among a set of overturned cards by revealing only two cards at a time. In our game, the players are asked to match a "physical card", which is an image of a scene in the real world, to a "digital card", which corresponds to a scene in a virtual world. The objective is to convey a mixed-reality sensation. Cards are matched with a scene identification engine which consists of multiple classifiers trained on previously collected images. We present our comprehensive overall game design, as well as implementation details and results. Additionally, we also describe how we constructed our scene identification engine and its performance. [ABSTRACT FROM AUTHOR]

In this paper, we present a robust approach to real-time tracking of multiple objects in mediated environments using a set of calibrated color and IR cameras. Challenges addressed in this paper include robust object tracking in the presence of color projections on the ground plane and partial/complete occlusions. To improve tracking in such complex environment, false candidates introduced by ground plane projection or mismatching of objects between views are removed by using the epipolar constraint and the planar homography. A mixture of Gaussian is learned using the expectation-maximization algorithm for each target to further refine the 3D location estimates. Experimental results demonstrate that the proposed approach is capable of robust and accurate 3D object tracking in a complex environment with a great amount of visual projections and partial/complete occlusions. [ABSTRACT FROM AUTHOR]

In this paper, we present a new approach to reconstruct 3D human motion from video clips with the assistance of a precaputred motion library. Given a monocular video clip recording of one person performing some kind of locomotion and a motion library consisting of similar motions, we can infer the 3D motion from the video clip. We segment the video clip into segments with fixed length, and by using a shape matching method we can find out from the motion library several candidate motion sequences for every video segment, then from these sequences a coarse motion clip is generated by performing a continuity test on the boundaries of these candidate sequences. We propose a pose deformation algorithm to refine the coarse motion. To guarantee the naturalness of the recovered motion, we apply a motion splicing algorithm to the motion clip. We tested the approach using synthetic and real sports videos. The experimental results show the effectiveness of this approach. [ABSTRACT FROM AUTHOR]

Videos are composed of shots, each of which is recorded continuously by a camera, and video editing can be considered as a process of re-sequencing shots selected from original videos. Shots usually include redundant segments, which are often edited out by professional editors. This paper proposes a method for automatically extracting appropriate segments to be included in edited videos from shots based on temporal patterns of audio and visual features in appropriate segments and redundant segments in example videos learned with Hidden Markov Models. The effectiveness of the proposed method is verified with experiments using original shots extracted from movies and appropriate segments extracted from movie trailers as example videos. [ABSTRACT FROM AUTHOR]

Digital photos are massively produced while digital cameras are becoming popular, however, not every photo has good quality. Blur is one of the conventional image quality degradation which is caused by various factors. In this paper, we propose a scheme to detect blurred images and classify them into several different categories. The blur detector uses support vector machines to estimate the blur extent of an image. The blurred images are further classified into either locally or globally blurred images. For globally blurred images, we estimate their point spread functions and classify them into camera shake or out of focus images. For locally blurred images, we find the blurred regions using a segmentation method, and the point spread function estimation on the blurred region can sort out the images with depth of field or moving object. The blur detection and classification processes are fully automatic and can help users to filter out blurred images before importing the photos into their digital photo albums. [ABSTRACT FROM AUTHOR]

Recently, for reusing large quantities of accumulated news video, technology for news topic searching and tracking has become necessary. Moreover, since we need to understand a certain topic from various viewpoints, we focus on identical event detection in various news programs from different countries. Currently, text information is generally used to retrieve news video. However, cross-lingual retrieval is complicated by machine translation performance and different viewpoints and cultures. In this paper, we propose a cross-lingual retrieval method for detecting identical news events that exploits image information together with text information. In an experiment, we verified the effectiveness of making use of the existence of near-duplicate video segments and the possibility of improving retrieval performance. [ABSTRACT FROM AUTHOR]

We propose a new Web image gathering system which employs a part-based object recognition method. The novelty of our work is introducing the bag-of-keypoints representation into an Web image gathering task instead of color histogram or segmented regions our previous system used. The bag-of-keypoints representation has been proven that it has the excellent ability to represent image concepts in the context of visual object categorization / recognition in spite of its simplicity. Most of object recognition work assumed that complete training data is available. On the other hand, in the Web image gathering task, since images associated with the given keywords are gathered from the Web fully-automatically, complete training images cannot be available. In this paper, we combine the HTML-based automatic positive training image selection and the bag-of-keypoints-based image selection with an SVM which is a supervised machine learning method. This combination enables the system to gather many images related to given concepts with high precision fully automatically needing no human intervention. Our main objective is to examine if the bag-of-keypoints model is also effective for the Web image gathering task where training images always include some noise. By the experiments, we show the new system outperforms our previous systems, other systems and Google Image Search greatly. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel query language for video indexing and retrieval that (1) enables to make queries both at the image level and at the semantic level (2) enables the users to define their own scenarios based on semantic events and (3) retrieves videos with both exact matching and similarity matching. For a query language, four main issues must be addressed: data modeling, query formulation, query parsing and query matching. In this paper we focus and give contributions on data modeling, query formulation and query matching. We are currently using color histograms and SIFT features at the image level and 10 types of events at the semantic level. We have tested the proposed query language for the retrieval of surveillance videos of a metro station. In our experiments the database contains more than 200 indexed physical objects and 48 semantic events. The results using different types of queries are promising. [ABSTRACT FROM AUTHOR]

3D motion capture is a form of multimedia data that is widely used in animation and medical fields (such as physical medicine and rehabilitation where body joint analysis is needed). These applications typically create large repositories of motion capture data and need efficient and accurate content-based retrieval techniques. 3D motion capture data is in the form of multi-dimensional time series data. To reduce the dimensions of human motion data while maintaining semantically important features, we quantize human motion data by extracting Spatial-Temporal Features through SVD and translate them onto a 1-dimensional sequential representation through our proposed sGMMEM (semantic Gaussian Mixture Modeling with EM). Thus, we achieve good classification accuracies for primitive human motion categories (walking 92.85%,run 91.42%,jump 94.11%) and even for subtle categories (dance 89.47%,laugh 83.33%,basketball signal 85.71%,golf putting 80.00%). [ABSTRACT FROM AUTHOR]

Although the variable-block-size motion compensation scheme significantly reduces the compensation error, the computational complexity of motion estimation (ME) is tremendously increased at the same time. To reduce the complexity of the variable-block-size ME algorithm, we propose a statistical learning approach to simplify the computation involved in the sub-MB mode selection. Some representative features are extracted during ME with fixed sizes. Then, an off-line pre-classification approach is used to predict the most probable sub-MB modes according to the run-time features. It turns out that only possible sub-MB modes need to perform ME. Experimental results show that the computation complexity is significantly reduced while the video quality degradation and bitrate increment is negligible. [ABSTRACT FROM AUTHOR]

In this paper we propose to use the normalized cross correlation (NCC) as the similarity measure for block-based motion estimation (ME) to replace the sum of absolute difference (SAD) measure. NCC is a more suitable similarity measure than SAD for reducing the temporal redundancy in video comparison since we can obtain flatter residual after motion compensation by using the NCC as the similarity measure in the motion estimation. The flat residual results in large DC term and smaller AC term, which means less information is lost after quantization. Thus, we can obtain better quality in the compressed video. Experimental results show the proposed NCC-based motion estimation algorithm can provide similar PSNR but better SSIM than the traditional full search ME with the SAD measure. [ABSTRACT FROM AUTHOR]

To achieve interactive speed, displacement mapping in the GPU is typically implemented in two steps: vertex shading/rasterization of the base surface and pixel shading. Pixel shading applies the height map relative to the image plane of the base surface, casts view rays to the height field through each pixel, finds the intersection point with the height field, and computes the color of that point. Here, the ray-casting process involves significant errors; The spatial relationship between the ray and the base surface is not preserved between the ray and the image plane of the base surface. The errors result in incorrect silhouettes. To address this problem, we curve the ray so that the spatial relationship between the (linear) ray and the base surface is preserved between the curved ray and the image plane of the base surface. This method reduces intersection errors, producing more satisfactory silhouettes, self-occlusions and shadows. [ABSTRACT FROM AUTHOR]

Music players for personal computers are often featured with music visualization by generating animated patterns according to the music's low-level features such as loudness and spectrum. This paper proposes an emotion-based music player which synchronizes visualization (photos) with music based on the emotions evoked by auditory stimulus of music and visual content of visualization. For emotion detection from photos, we collected 398 photos with their emotions annotated by 496 users through the web. With these annotations, a Bayesian classification method is proposed for automatic photo emotion detection. For emotion detection from music, we adopt an existing method. Finally, for composition of music and photos, in addition to matching high-level emotions, we also consider low-level feature harmony and temporal visual coherence. It is formulated as an optimization problem and solved by a greedy algorithm. Subjective evaluation shows emotion-based music visualization enriches users' listening experiences. [ABSTRACT FROM AUTHOR]

This paper introduces our LightCollabo system which is a distant collaboration tool designed for manufacturers. For distant collaboration between factory workers and members of a product design team, it is important to support interactive discussion over actual objects. LightCollabo enables remotely located people to share a view of actual objects and to annotate on the objects by using a camera and a projector whose optic axes and view angles are precisely aligned. LightCollabo has been experimentally deployed in several locations in China and Japan and proven to be effective. Initial results of our use case study are also described. [ABSTRACT FROM AUTHOR]

JPEG2000 has been selected as the image compression and decompression technology for digital cinema by DCI(Digital Cinema Initiatives). In a few years, large amount of JPEG2000 compressed files will be widely used and delivered. Identifying a target compressed file out of image sequences or database is highly demanded. In this paper, very unique identifying method is presented. It takes advantage of the feature of JPEG2000 codestream structure. The proposed method has advantages of low computation and high accuracy over conventional methods. [ABSTRACT FROM AUTHOR]

Transmission of highly compressed video bitstreams can result in packet erasures when channel status is unfavorable. Spatial error concealment (SEC) techniques are very useful in the recovery of impaired video sequences, especially in the presence of scene changes, irregular motion, and appearance or disappearance of objects. As errors occur in the first frame, the corrupted MBs must be recovered by utilizing SEC schemes in order to prevent the propagation of errors to the succeeding inter-coded frames. We propose two SEC methods; one conceals the variances of the different kinds of damaged Macroblocks (MBs) targeted at any condition, and the other is speed-up which utilizes a H.264 coding tool, directional spatial intra prediction, in order to conceal the entire spectrum of damaged MBs targeted at intra-coded block(s). The experimental results show that when compared to other state of the art methods, our proposed SEC techniques significantly improve video quality up to 3.62 - 4.22 dB while reducing computational complexity. [ABSTRACT FROM AUTHOR]