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International audience; MPEG-7 has emerged as the standard for multimedia data content description for efficiently describing multimedia content. In this context, its primary goal is to provide flexible and effective searching and retrieval of multimedia resources. Most of the earlier work on MPEG-7 description schemes (DSs) and descriptors (Ds) focuses on the description of a single multimedia document, whereas MPEG-7 can be further exploited to support more advances implementations under multimedia database systems. Therefore, it is important to reconsider issues related to high level multimedia modeling and representation, in the light of the MPEG-7 perspective. In this paper, we propose a high level multimedia representation and description scheme based on multi-level video modeling and semantic video classification. The proposed multi-level multimedia representation and DSs are expected to support more effective video content indexing and accessing operations. The presented DSs and Ds are further described by using the XML Schema language, which has been adopted as the basis of the Description Definition Language (DDL) of the MPEG-7 standard.

Automatic semantic video object extraction is an important step for providing content-based video coding, indexing and retrieval. However, it is very difficult to design a generic semantic video object extraction technique, which can provide variant semantic video objects by using the same function. Since the presence and absence of persons in an image sequence provide important clues about video content, automatic face detection and human being generation are very attractive for content-based video database applications. For this reason, we propose a novel face detection and semantic human object generation algorithm. The homogeneous image regions with accurate boundaries are first obtained by integrating the results of color edge detection and region growing procedures. The human faces are detected from these homogeneous image regions by using skin color segmentation and facial filters. These detected faces are then used as object seed for semantic human object generation. The correspondences of the detected faces and semantic human objects along time axis are further exploited by a contour-based temporal tracking procedure.

In many image processing applications, edge detection is a useful method for obtaining a simplified image that preserves the domain geometric structures and spatial relationships among variant image components. For providing automatic edge detection, two problems should be solved: one is feature extraction for calculating the edge strength, another is feature classification for automatic edge detection. For solving these two problems, we propose an improved automatic edge detection technique. Three color components of a color image and more potential edge patterns are integrated for solving the feature extraction problem. A fast entropic thresholding technique is also developed for solving the feature classification problem. Experimental results have confirmed that this proposed edge detector can provide more reasonable results as compared with the traditional isotropic edge operators, and its calculation cost has been reduced as compared with the complex edge detectors. Good balance between the calculation cost and the edge detection accuracy is achieved.

Data quality has many dimensions one of which is accuracy. Accuracy is usually compromised by errors accidentally or intensionally introduced in a database system. These errors result in inconsistent, incomplete, or erroneous data elements. For example, a small variation in the representation of a data object, produces a unique instantiation of the object being represented. In order to improve the accuracy of the data stored in a database system, we need to compare them either with real-world counterparts or with other data stored in the same or a different system. In this paper, we address the problem of matching records which refer to the same entity by computing their similarity. Exact record matching has limited applicability in this context since even simple errors like character transpositions cannot be captured in the record-linking process. Our methodology deploys advanced data-mining techniques for dealing with the high computational and inferential complexity of approximate record matching.

In previous work, we proposed an m-level hierarchical multiprocessor system. The proposed system reduces the network complexity by employing m levels of hierarchy. The system performance was analyzed, and the results showed that, for a higher rate of local requests, the system performed close to the crossbar system, and better than a typical multiple-bus system (with the number of buses equal to half the number of processors). In this paper, we study the effect of failures on the performance of the m-level hierarchical multiprocessor systems. We develop analytical modeling techniques to compute the reliability and the bandwidth availability of the m-levelsystem, for hierarchically nonuniform reference (HNR) and uniform reference (UR) models. The results obtained for the m-level system are compared with those of the crossbar and multiple-bus systems.

Autonomous multidatabases, Computer Aided Design (CAD) databases, and Object Oriented Databases have requirements which traditional transactions cannot meet. Users of these advanced applications are more sophisticated than users envisioned for On Line Transaction Processing (OLTP) applications a few decades ago. The need to relax the properties of complex database transactions is urgent. Frameworks for flexible transaction systems are needed. This paper is a step towards this objective. This paper addresses the formalization of a new transaction model called Flex transactions, along with execution control and analysis protocols. The algorithm is formalized through the use of Predicate Transition Nets (PTN) and reachability trees.

Quasi serializability is a correctness criterion for multidatabase consistency. An execution is quasi serializable if its local executions are serializable and it is equivalent to a quasi serial execution in which global transactions are executed sequentially. In this paper, we study the integrity aspects of quasi serializability. The main result is that, if each transaction is integrity preserving, quasi serializable executions preserve local integrity constraints and global constraints that involve data updatable by global transactions only.

Research in the area of concurrency-control performance evaluation has been extensive in the past few years. Unfortunately, conclusions arrived at by many of the researchers were incomparable and at times contradictory, because of the different assumptions and performance models used. Therefore, a unified and complete performance model is needed. We propose a framework for concurrency-control performance evaluation in single-site databases. Areas of performance studies are classified, and a performance model is suggested. Finally, we give a complete example of a performance study for the dynamic two-phase locking algorithm using this framework. Two effects were studied: those of granularity and the read-write mix.