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This paper presents paper retrieval using the specific paper features chain and laid lines. Paper features are detected in digitized paper images and they are represented such that they could be used for retrieval. Optimal retrieval performance is achieved by means of a trainable similarity measure for a given set of paper features. By means of these methods a retrieval system is developed that art experts could use real-time in order to speed up their paper research. [ABSTRACT FROM AUTHOR]

Paper keeps as a key information medium and this has motivated the development of new technologies for digitally augmented paper (DAP) that enable printed content to be linked with multimedia information. Among those technologies, one simplest approach is to print some visible patterns on paper (e.g., barcodes in the margin) as cross-media links. Due to the latest progress in printing industry, some more sophisticated methods have been developed, that is, some kinds of patterns printed on the background of a page in a high resolution are almost invisible and then we are affected little when reading. For all these pattern-embedding based approaches to integrate printed and multimedia information, we aim to present a unified publishing framework independent of particular patterns and readers(e.g., cameras to capture patterns) used to realize DAP. The presented framework manages semantic information about printed documents, multimedia resources, and patterns as links between them and users are provided with a platform for publishing DAP documents. [ABSTRACT FROM AUTHOR]

We describe a new binning technic for informed data hiding problem. In information theoretical point of view, the blind watermarking problem can be seen as transmitting a secret message M through a noisy channel on top of an interfered host signal S that is available only at the encoder. We propose an embedding scheme based on Low Density Parity Check(LDPC) codes, in order to quantize the host signal in an intelligent manner so that the decoder can extract the hidden message with a high probability. A mixture of erasure and symmetric error channel is realized for the analysis of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes a kind of remote rendering method based on awareness model. This method takes the additional cost caused by the movement of the viewpoint into cost calculation and designs a cost prediction algorithm based on the vision field divided by awareness model. The simulation results show that the improved method can not only improve the quality of the remote rendering, but also make full use of the bandwidth of the network, as well as make the remote rendering more fluent when the viewpoint moves fast. [ABSTRACT FROM AUTHOR]

MPEG-4 system defines a binary format, called BIFS(BInary Format for Scene), and textual format, called XMT(eXtensible MPEG-4 Textual format) to represent the composition information of the scene featuring interactive content. BIFS was proposed for efficient transmission, and XMT based on XML, with the aim to support various playing environments and to enhance the reusability of the contents as it is converted into languages such as VRML, SMIL and etc. To provide interoperability of this XMT, this paper proposes the mechanism to convert XMT into SMIL using XSLT(XML Stylesheet Language Transformation). Further, this paper analyzes XMT and SMIL to propose a conversion method for various nodes, which do not match one to one, and defines XSLT for conversion. In addition, this paper represents various geometric objects that are not supported in the SMIL using SVG(Scalable Vector Graphics). [ABSTRACT FROM AUTHOR]

H.264/AVC is the newest international video coding standard. This paper presents a novel hardware design for CABAC decoding in H.264/AVC. CABAC is the key innovative technology, but it brings huge challenge for high throughput implementation. The current bin decoding depends on the previous bin, which results in the long latency and limits the system performance. In this paper, the data hazards are analyzed and resolved using the algorithmic features. We present a new pipeline-based architecture using the standard look-ahead technique where the arithmetic decoding engine works in parallel with the context maintainer. An efficient finite state machine is developed to match the requirement of the pipeline controlling and the critical path is optimized for the timing. The proposed implementation can generate one bin per clock cycle at the 160-MHz working frequency. [ABSTRACT FROM AUTHOR]

Automatic story unit segmentation is an essential technique for content based video retrieval and summarization. A good video story unit has complete content and natural boundary in visual and acoustic perception, respectively. In this paper, a method of acoustic perception friendly story unit segmentation for broadcast soccer video is proposed. The approach combines replay detection, view pattern and non-speech detection to segment story units. Firstly, a replay detection method is implemented to find the highlight events in soccer video. Secondly, based on positions of replay clips, an FSM (Fine State Machine) is used to obtain rough starting points of story units. Finally, audio boundary alignment is employed to locate natural audio boundaries for acoustic perception. The algorithm is tested on several broadcast soccer videos. The story units segmented by algorithms with and without audio alignment are compared in acoustic perception. The experimental results indicate the performance of the proposed algorithm is encouraging and effective. [ABSTRACT FROM AUTHOR]

Supporting multimedia search has emerged as an important research topic. There are three paradigms on the research spectrum that ranges from the least automatic to the most automatic. On the far left end, there is the pure manual labeling paradigm that labels multimedia content, e.g., images and video clips, manually with text labels and then use text search to search multimedia content indirectly. On the far right end, there is the content-based search paradigm that can be fully automatic by using low-level features from multimedia analysis. In recent years, a third paradigm emerged which is in the middle: the annotation paradigm. Once the concept models are trained, this paradigm can automatically detect/annotate concepts in unseen multimedia content. This paper looks into this annotation paradigm. Specifically, this paper argues that within the annotation paradigm, the relationship-based annotation approach outperforms other existing annotation approaches, because individual concepts are considered jointly instead of independently. We use two examples to illustrate the argument. The first example is on image annotation and the second one is on video annotation. Experiments indeed show that relationship-based annotation approaches render superior performance. [ABSTRACT FROM AUTHOR]

A novel method for automatic occluded targets recognition in SAR images is proposed in this paper. Different SAR occluded targets are simulated based on actual vehicles from the MSTAR database, and are recognized using SVM classifier by grouping recognition based on the targets azimuth angles. It is shown that the proposed method outperforms the typical methods in accuracy at high occlusion, and robustness to occlusion with experiments considering accuracy and confusion matrix. [ABSTRACT FROM AUTHOR]

In this paper we propose a novel feature extracting method based on spatiotemporal slice analyzing. To date, video features are focused on the character of every single video frame. With our method, the video content is no longer represented with every single frame. The temporal variation of visual information is taken as an important feature of video in our method. We examined this kind of feature with experiments in this paper. The experiment results show that the proposed feature is effective and robust for variant video content and format. [ABSTRACT FROM AUTHOR]

Over the years, multimedia applications are getting increasingly more complex and large in scale. Multimedia Web Service is identified as one of the possible solutions to meet the challenges. The advantages of using Web Services are ease of application development, adaptive to changes, fault tolerance and etc. In the paper, a sample tracking application will be discussed and developed using multimedia Web Services (multimediaWS) approach. Throughout the paper, we will suggest some general rules on designing the multimediaWS as well as evaluate the pros and cons of using multimediaWS for multimedia application. [ABSTRACT FROM AUTHOR]

A method of shadow removal from sole uncalibrated outdoor image is proposed. Existing approaches usually decompose the image into albedo and illumination images, in this paper, based on the mechanism of shadow generation, the occlusion factor is introduced, and the illumination image is further decomposed as the linear combination of solar irradiance and ambient irradiance images. The involved irradiance are achieved from the user-supplied hints. The shadow matte are evaluated by the anisotropic diffusion of posterior probability. Experiments show that our method could simultaneously extract the detailed shadow matte and recover the texture beneath the shadow. [ABSTRACT FROM AUTHOR]

This paper presents techniques for retrieving photos from personal memories collections using generic concepts that the users specify. It is part of a larger project for capturing, storing, and retrieving personal memories in different contexts of use. Semantic concepts are obtained by training binary classifiers using the Regularized Least Squares Classifier (RLSC)and can be combined to express more complex concepts. The results that were obtained so far are quite good and by adding more low level features, better results are possible. The paper describes the proposed approach, the classifier and features, and the results that were obtained. Keywords: multimedia retrieval, personal memories, classification based on kernel. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the parameter identification problem, one of the most essential problems in the 3D cloth animation created by multimedia software. We present a novel interactive parameter identification framework which integrates the industry knowledge. The essential of this paper is that we design a hybrid intelligent learning system using statistical analysis of kawabata evaluation system(KES) data from fabric industry database, fuzzy system and radial basis function(RBF) neural networks. By adopting our method the 3D cloth animator can interactively identify the parameters of cloth simulation with subjective linguistic variables while in the past decades it is very difficult for cloth animators to tune the parameters. We solve the 3D cloth parameter problem using the intelligent knowledge integration method for the first time in the multimedia and graphics research area and our method is applied to the most popular 3D tool Maya. The experimental results illustrate the practicability and expansibility of this method. Keywords: Interactive parameter identification, 3D Cloth Animation, Kawabata evaluation system, Fuzzy system, RBF Neural network. [ABSTRACT FROM AUTHOR]

H.264 video standard, in spite of its high quality, is too time-consuming for widespread acceptance in video applications, mainly due to its computationally complex motion estimation (ME). To reduce this complexity, we propose motion continuity hypothesis, which means that all motion vectors (MVs) of a block are usually located in a small area. This area is formalized as modified valid region (MVR), an improved version of valid region which is proposed by the present authors in a previous paper. Then, this paper develops a new fastME algorithm for H.264, called MVR-based fast ME (MVRF), which searches only a much smaller area in reference frames(RFs) for motion estimation than full searchH.264 does, so it reduces up to 43% search pixels. MVRF is so deliberately chosen that on average, up to 98% MVs determined by MVRF coincide with those by full search H.264, therefore keeping the recovery quality and bit-rate almost the same as those of full search H.264. [ABSTRACT FROM AUTHOR]

This paper addresses an image fingerprinting scheme for the print-to-capture model performed by a photo printer and digital camera. When capturing an image by a digital camera, various kinds of distortions such as noise, geometrical distortions, and lens distortions are applied slightly and simultaneously. In this paper, we consider several steps to extract fingerprints from the distorted image in print-and capture scenario. To embed ID into an image as a fingerprint, multi-bits embedding is applied. We embed 64 bits ID information as a fingerprint into spatial domain of color images. In order to restore a captured image from distortions a noise reduction filter is performed and a rectilinear tiling pattern is used as a template. To make the template a multi-bits fingerprint is embedded repeatedly like a tiling pattern into the spatial domain of the image. We show that the extracting is successful from the image captured by a digital camera through the experiment. [ABSTRACT FROM AUTHOR]

Multimedia communication systems are rapidly developed during the last decade to reach the technology of streaming applications. Work in this paper analyzes and evaluates the area of multimedia communication services over highspeed networks. The main target is to test the multimedia communication from the applications perspective. This means to test multi-source multi-destination communication and the inter-behavior of multimedia traffic in such an environment. We run a simulation study to examine the network behavior in case of a QoS-enabled architecture, and to introduce establishing the different multi-participant scenarios in multiparty applications. The simulation study in this paper focuses on the inter-effect of varying traffic types generated by distributed traffic sources and injected to distributed groups of destinations. The simulation study examines the responsiveness and performance behavior of the interactive multimedia communication session in the support of QoS architecture with emphasis on DiffServ and MPLS networks. [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]

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]

This paper has discussed how to use feature and topology information to compare 3D CAD models represented by polygonal meshes. In this work we propose an enhanced method to compare CAD models based on shape distributions. A topology-preserving simplification method of polygonal meshes was used to simplify CAD model as the pretreatment for generation of sample points. We improved the method of sampling points and a pair of shape functions more sensitive to shape was employed to construct a 2D shape distribution. The experiential results showed that simplification has a positive effort on shape comparison and our method achieved more effective performance than the conventional one. [ABSTRACT FROM AUTHOR]

Streaming media has contributed to a significant amount of today's Internet Traffic. One solution of to solve this problems is using streaming proxy. There are two categories in streaming proxy; that is for homogeneous and heterogeneous client. The transcoding proxy can be used for heterogeneous client. The traditional proxy considers only a single version of the objects, whether they are to be cached or not. However the transcoding proxy has to evaluate the aggregate effect from caching multiple versions of the same object to determine an optimal set of cache objects. And recent researches about multimedia caching frequently store initial parts of videos on the proxy to reduce playback latency and archive better performance. Also lots of researches manage the contents with segments for efficient storage management. In this paper, we propose the efficient proxy policy that combines the segment-based caching mechanism and aggregate effect at transcoding proxy. The results demonstrate that the proposed algorithm outperforms in delay time, byte-hit ratio and the amount of transcoding data than other methods. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new technique for extracting salient regions in an image. Identification of salient regions is useful for region/object based image processing. Previous works on salient regions/points typically involve complex detection and are not always reliable in terms of perceptual importance and robustness. This paper presents an efficient salient-region extraction algorithm based on the significance of accumulated wavelet coefficients. The proposed method is robust to common image processing such as compression, filtering, and geometric distortions. Experimental results substantiate the distinguished performance of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we propose a hybrid content-based image authentication scheme that integrates two complementary algorithms: Robust content-based authentication and semi-fragile crypto-hash based authentication. The former uses global features and is quite robust against various types of noise. The latter uses local features and therefore is able to identify the tempered area in case the image is attacked. The proposed scheme takes advantage from both algorithms and provides more information to guide the decision maker. In addition, we also propose two improved algorithms based on Fridrich's content-based and Sun's crypto-hash based authentication. Experiments show that the improved algorithms are more secure than the original algorithms. Another contribution of this paper is that, by concatenating the signatures generated with two different authentication algorithms, the fuzzy area in authentication decision can be further quantized, which provides more choices for authentication decision. [ABSTRACT FROM AUTHOR]

Many researchers try to utilize the semantic information extracted from visual feature to directly realize the semantic video retrieval or to supplement the automated speech recognition (ASR) text retrieval. But bridging the gap between the low-level visual feature and semantic content is still a challenging task. In this paper, we study how to effectively use Latent Semantic Indexing (LSI) to improve the semantic video retrieval through the ASR texts. The basic LSI method has been shown effective in the traditional text retrieval and the noisy ASR text retrieval. In this paper, we further use the lexicon-guided semantic clustering to effectively remove the noise introduced by news video's additional contents, and use the cluster-based LSI to automatically mine the semantic structure underlying the terms expression. Tests on the TRECVID 2005 dataset show that the above two enhancements achieve 21.3% and 6.9% improvements in performance over the traditional vector-space model(VSM) and the basic LSI separately. [ABSTRACT FROM AUTHOR]

This paper presents a study about the application of Zernike invariants to content-based Image Retrieval for 2D color images. Zernike invariants have been chosen because of their good performance for object recognition. Taking into account the good results achieved in previous CBIR experiments with color based primitives using a multiresolution representation of the visual contents, this paper presents the application of a wavelet transform to the images in order to obtain a multiresolution representation of the shape based features studied. Experiments have been performed using two databases: the first one is a small self-made 2D color database formed by 298 RGB images and a test set with 1655 query images that has been used for preliminary tests; the second one is Also experiments using the Amsterdam Library of Object Images (ALOI), a free access database. Experimental results show the feasibility of this new approach. [ABSTRACT FROM AUTHOR]

Wyner-Ziv video coding has become one of the hottest research topics in the video coding community due to the conceptual, theoretical and functional novelties it brings. Among the many practical architectures already available, feedback channel-based with channel coding, e.g. LDPC and turbo codes, solutions are rather popular. These solutions rely on decoder motion estimation based on periodic Intra coded key frames, setting the so-called GOP size, very much like in conventional video coding. This paper targets the rate-distortion and complexity performance study of this type of Wyner-Ziv coding solution as a function of the GOP size, considering both LPDC and turbo codes. [ABSTRACT FROM AUTHOR]

This paper investigates an extension of the SP picture from the H.264/AVC to the scalable video coding (SVC), which has been recently developed and standardized as the scalable extension of the H.264/AVC. In comparison with the scalable profiles of previous video coding standards, the SVC has achieved significant improvement in both coding efficiency and scalability in temporal, spatial and fidelity, which efficiently provides coded stream wide adaptivity to dynamic network conditions as well as diverse clients. In communication environments, this efficient adaptivity can be provided by bit stream switching between different scalable layers. The current SVC supports bit stream switching only at instantaneous decoding refresh (IDR) access unit. However, in order to provide instantaneous switching capability, the IDR picture needs to be frequently coded in the SVC stream, which dramatically decreases the coding efficiency. Therefore, SP picture for the SVC is proposed in this paper for efficient bit stream switching. Performance analysis shows that the SP picture for the SVC provides an average 1.2 dB PSNR enhancement over the IDR picture while providing similar functionalities. [ABSTRACT FROM AUTHOR]

This paper considers the problem of Bayesian inference in dynamical models with time-varying dimension. These models have been studied in the context of multiple target tracking problems and for estimating the number of components in mixture models. Traditional solutions for the single target tracking problem becomes infeasible when the number of targets grows. Furthermore, when the number of targets is unknown and the number of observations is influenced by misdetections and clutter, then the problem is complex. In this paper, we consider a marked Poisson process for modeling the time-varying dimension problem. Another solution which has been proposed for this problem is the Probability Hypothesis Density (PHD) filter, which uses a random set formalism for representing the time-varying nature of the state and observation vectors. An important feature of the PHD and the proposed method is the ability to perform sensor data fusion by integrating the information from the multiple observations without an explicit data association step. However, the method proposed here differs from the PHD filter in that uses a Poisson point process formalism with discretized spatial intensity. The method can be implemented with techniques similar to the standard particle filter, but without the need for specifying birth and death probabilities for each target in the update and filtering equations. We show an example based on ultrasound acoustics, where the method is able to represent the physical characteristics of the problem domain. [ABSTRACT FROM AUTHOR]

Image registration based on landmarks and radial basis functions (e.g. thin plate splines) results in global changes and deformation spreads over the entire resampled image. This paper presents a radial basis function for registration of local changes. The proposed research was based on study/analysis of profile for different radial basis functions, supporting local changes. The proposed function was designed to overcome the weaknesses, observed in other radial basis functions. The results are analyzed/compared on the basis of different properties and parameters discussed in this paper. Experimental results show that the proposed function improves the registration accuracy. [ABSTRACT FROM AUTHOR]

Casting is one of the most important processes in the manufacture of parts for various kinds of industries, among which the automotive industry stands out. Like every manufacturing process, there is the possibility of the occurrence of defects in the materials from which the parts are made, as well as of the appearance of faults during their operation. One of the most important tools for verifying the integrity of cast parts is radioscopy. This paper presents pattern recognition methodologies in radioscopic images of cast automotive parts for the detection of defects. Image processing techniques were applied to extract features to be used as input of the pattern classifiers developed by artificial neural networks. To estimate the accuracy of the classifiers, use was made of random selection techniques with sample reposition (Bootstrap technique) and without sample reposition. This work can be considered innovative in that field of research, and the results obtained motivate this paper. [ABSTRACT FROM AUTHOR]

The performance of Support Vector Machines, as many other machine learning algorithms, is very sensitive to parameter tuning, mainly in real world problems. In this paper, two well known and widely used SVM implementations, Weka SMO and LIBSVM, were compared using Simulated Annealing as a parameter tuner. This approach increased significantly the classification accuracy over the Weka SMO and LIBSVM standard configuration. The paper also presents an empirical evaluation of SVM against AdaBoost and MLP, for solving the leather defect classification problem. The results obtained are very promising in successfully discriminating leather defects, with the highest overall accuracy, of 99.59%, being achieved by LIBSVM tuned with Simulated Annealing. [ABSTRACT FROM AUTHOR]

This paper presents a novel spatial-invariant filtering method for rendering focus effects without aliasing artifacts from undersampled light fields. The presented method does not require any scene analysis such as depth estimation and feature matching. First, we generate a series of images focused on multiple depths by using the conventional synthetic aperture reconstruction method and treat them as a 3D image. Second we convert it to the alias-free 3D image. This paper shows this conversion can be achieved simply by a 3D filtering in the frequency domain. The proposed filter can also produce depth-of-field effects. [ABSTRACT FROM AUTHOR]

A new and efficient method for combining iris biometrics with custom cryptographic schemes to obtain an efficient biocryptosystem is proposed in this paper. Though the method structure is basically derived from a previously described biocryptosystem scheme, the introduction of new image processing methods alongside with efficient utilization of traditional methods show promising developments compared with the previous biocryposystem especially in the field of generating longer cryptographic key strings while keeping the system quality [ABSTRACT FROM AUTHOR]

In a process of insect footprint recognition, footprint segments need to be extracted from scanned insect footprints in order to find out appropriate features for classification. In this paper, we use a clustering method in a preprocessing stage for extraction of insect footprint segments. In general, sizes and strides of footprints may be different according to type and size of an insect for recognition. Therefore we propose a method for insect footprint segment extraction using an improved ART2 algorithm regardless of size and stride of footprint pattern. In the improved ART2 algorithm, an initial threshold value for clustering is determined automatically using the contour shape of the graph created by accumulating distances between all the spots within a binarized footprint pattern image. In the experimental results, applying the proposed method to two kinds of insect footprint patterns, we illustrate that clustering is accomplished correctly. [ABSTRACT FROM AUTHOR]

As the amount of visual information is rapidly increasing, users want to find the more semantic information easily. Most retrieval systems by low-level features(such as color, texture) could not satisfy user's demand. To interpret semantic of image, many researchers use keywords as textual annotation. However, it's the image retrieval without ranking by text matching which is the simplest way to retrieval according to keyword's existence or nonexistence. In this paper, we propose conceptualization by similarity measure using relations among keywords for efficient image retrieval. We experiment annotated image retrieval by lowering the unrelated keyword's weight value and raising important keyword's one. [ABSTRACT FROM AUTHOR]

The H.264 video coding standard provides considerably higher coding efficiency than those of previous standards but its complexity is significantly increased. In this paper, we propose an efficient method of fast mode decision by exploiting spatio-temporal correlation in H.264. Firstly, we select skip mode or inter mode by considering the temporal correlation. Secondly, we select variable block size on inter mode by considering the spatial correlation. Simulations show that the proposed method reduces the encoding time by 71% on average without any significant PSNR losses. [ABSTRACT FROM AUTHOR]

Traditional boosting method like adaboost, boosts a weak learning algorithm by updating the sample weights (the relative importance of the training samples) iteratively. In this paper, we propose to integrate feature re-weighting into boosting scheme, which not only weights the samples but also weights the feature elements iteratively. To avoid overfitting problem caused by feature re-weighting on a small training data set, we also incorporate relevance feedback into boosting and propose an interactive boosting called i.Boosting. It merges adaboost, feature re-weighting and relevance feedback into one framework and exploits the favorable attributes of these methods. In this paper, i.Boosting is implemented using Adaptive Discriminant Analysis (ADA) as base classifiers. It not only enhances but also combines a set of ADA classifiers into a more powerful one. A feature re-weighting method for ADA is also proposed and integrated in i.Boosting. Extensive experiments on UCI benchmark data sets, three facial image data sets and COREL color image data sets show the superior performance of i.Boosting over AdaBoost and other state-of-the-art projection-based classifiers. [ABSTRACT FROM AUTHOR]

Scalar multiplication dP and gP+hQ are important in encryption, decryption and signature in information security and wireless network. The speed of computation of scalar multiplication is significant for related applications. In this paper, a new signed binary representation (SBR) for integers called complementary code method (CC) is proposed, which has minimum weight and needs less memory. An efficient algorithm using CC method for computing dP is shown also. According to analyzing and comparing to the other methods, this algorithm is the better one in window methods and is the simplest for applying in software and hardware. By applying joint representation in computing gP+hQ, new algorithm using CC method has the least joint weight compared to other methods mentioned in this paper. So, the new SBR can efficiently speed up the computation of scalar multiplication dP and gP+hQ and can be widely used in secure communication for improving the speed of encryption and signature. [ABSTRACT FROM AUTHOR]

A novel embedded processor element basing on the Transport Triggered Architecture is presented in this paper. The processor element consisting of two powerful arithmetic clusters using the application specific instruction processor design methodology achieves higher performance and is especially good at exploiting the instruction level and data level parallelisms in the multimedia applications. To improve the efficiency, the processor also presents the decoupled stream memory system with the characteristics of the stream buffer proxy to support the cross-line indexed accesses and to enhance the memory bandwidth. Then, a heterogeneous multiprocessor SoC chip involving the embedded processor is fabricated using 0.13um CMOS process, and the SoC operates at 400MHz and consumes only around 690mW. Experimental results show that the embedded processor element has good performance improvement for the multimedia applications. [ABSTRACT FROM AUTHOR]

In recent years, with the rapid growth of the Internet as well as the increasing demand for broadband services, live pay-television broadcasting via internet has become a promising business. To get this implemented, it is necessary to protect distributed contents from illegal copying and redistributing after they are accessed. Fingerprinting system is a useful tool for it. This paper shows that the anti-collusion code has advantages over other existing fingerprinting codes in terms of efficiency and effectivity for live pay-television broadcasting. Next, this paper presents how to achieve efficient and effective anti-collusion codes based on affine plane and unital, which are two known examples of balanced incomplete block design (BIBD). Meanwhile, performance evaluations of anti-collusion codes generated from affine plane and unital are conducted. Their practical explicit constructions are given last. [ABSTRACT FROM AUTHOR]

This paper describes a novel object mining system for videos. An algorithm published in a previous paper by the authors is used to segment the video into shots and extract stable tracks from them. A grouping technique is introduced to combine these stable tracks into meaningful object clusters. These clusters are used in mining similar objects. Compared to other object mining systems, our approach mines more instances of similar objects in different shots. The proposed framework is applied to a full length feature film and improved results are shown. [ABSTRACT FROM AUTHOR]

By reviewing DRMs up to now and two typical examples - AVS DRM and DMP IDP, the paper tries to find out the fundamental challenge of content protection approach from technical and social viewpoints. Not only it is difficult to deploy and update content encryption and security infrastructure, but also the content diffusion is limited and Fair Use is affected. The new schema for DRM should be content monitoring system in public space that prevents illegal diffusion of content in copyright but permits content being used freely in private space or for social liberty. The traditional rights in analog times will fluently move to digital space under the proposed schema. [ABSTRACT FROM AUTHOR]

Although content-based image retrieval has been studied for decades, most commercial image search engines are still text-based. However, there is a growing demand for techniques to support content-based image search at Web scale. In this paper, we propose an ambitious goal to searching one billion Web images by content, and discuss the major challenges and opportunities. We also present several important applications that can be greatly benefited by techniques to enable Web-scale image search by content. These applications include image copyright infringement detection, street-side photo search, and search-based image annotation. We believe that the insights presented in the paper are enlightening to researchers in this field, and any breakthrough we make in this space will lead to many impactful applications in the future. [ABSTRACT FROM AUTHOR]

In this presentation for the panel at MCAM07, I put forward the transition of modeling the world as was done on a large scale in computer vision before the year 2000, to the current situation where there have been considerable successes with multimedia analysis by learning from the world. We make a plead for the last type of learned features, modeling only the scene accidental conditions and learning the object or object class intrinsic properties. In this paper, in respect to contributions by many others, we illustrate the approach of learning features by papers from our lab at the University of Amsterdam. [ABSTRACT FROM AUTHOR]

In this paper, the performance of a wireless communication system based on the TD-CDMA transmission technique is analyzed. In this paper, we present simulation results for the performance of a turbo coded TD-CDMA system with QPSK over Rayleigh fading channel model. And the system performance employing the simple averaging channel estimation is compared to the ideal case with the perfect channel estimation. [ABSTRACT FROM AUTHOR]

In this study, the surveyed Trip Length Frequency Distribution (TLFD)is determined as a criterion for the reliability of evaluating the true O/D matrix. The surveyed TLFD can be used to check the similarity between the surveyed (true) Trip Length Distribution and the Trip Length Distribution of the estimated O/D matrix by the traffic counted models. When the surveyed TLFD is similar to the estimated TLFD, the reliability and correctness of the estimated O/D are high. Therefore, the objective of this paper is the development of the travel demand (O/D matrix) estimation using traffic counts on the large-scaled network. The Gradient Method is used for the model and the multi-class assignment technique is used for the equilibrium loading procedure in the model. This leads to the good guideline to the usage of the traffic count based O/D estimation in practice and gives a confidence to the transport planner. It is because the traffic counted O/D estimation models gives multiple solutions by its characteristics. In this paper we analyze the merits and demerits in each of a single-class based model and a multi-class based model in a large scale network. As a result, we have concluded that the multi-class based model has a closer value to the surveyed (true) TLFD than the TLFD of the estimated O/D matrix by the single-class based gradient method. [ABSTRACT FROM AUTHOR]

This paper develop the complexity reduction schemes of real root method that is mainly used in the CELP (Code Excited Linear Prediction) vocoder. The real root method is that if polynomial equations have the real roots, it is able to find those and transform them into LSP (Line Spectrum Pairs). Proposed algorithm is developed by using Mel scale and is to reduce the LSP complexity That is, the searching interval is arranged by using Mel scale but not it is uniform. In experimental results, complexity of the developed algorithm is reduced about 46% in average, but the transformed LSP parameters of the proposed method were the same as those of real root method. Hence, in case of applying proposed algorithm in G.723.1 (6.3kbps MP-MLQ), the speech quality is no distortion compared to original speech quality. [ABSTRACT FROM AUTHOR]

With the rapid development of wireless multimedia communication and Peer-to-Peer overlay network, it is envisioned that building a content and location addressable overlay network for wireless multimedia communication is promising. In this paper, based on a special structure, Geographically Hierarchical Index (GHI), we propose an efficient algorithm, Content and Location Addressable overlay Network (CLAN) algorithm, which makes p2p multimedia communication over MANETs applicable and efficient, satisfying three goals: efficiency, scalability and adaptability to node movement. [ABSTRACT FROM AUTHOR]

Energy consumption is a key issue in modern microprocessor system design in general, and in the design of mobile computing devices more in particular. This paper introduces a novel approach to energy-efficient media stream decoding that is based on the notion of media stream similarity. The key idea is that platform-independent scenarios of similar decode complexity can be identified within and across media streams. A client decoding a media stream annotated with scenario information can then adjust its processor clock frequency and voltage level based on these scenarios for reduced energy consumption. Our evaluation done using the AVC decoder and 12 reference streams shows an average energy reduction of 46% while missing less than 0.2% of the frame deadlines on average. [ABSTRACT FROM AUTHOR]

Feature extraction is one of the most important problems in face recognition task. In this paper, we use kernel uncorrelated discriminant analysis to extract the optimal discriminant features for face recognition. The method also solves the so-called "Small Sample Size" (SSS) problem, which exists in most Face Recognition tasks. Experimental results on the Yale face database and AT&T face database show the effectiveness of this method. [ABSTRACT FROM AUTHOR]