15256739
Performance prediction for individual recognition by gait
Existing gait recognition approaches do not give their theoretical or experimental performance predictions. Therefore, the discriminating power of gait as a feature for human recognition cannot be evaluated. In this paper, we first propose a kinematic-based approach to recognize human by gait. The proposed approach estimates 3D human walking parameters by performing a least squares fit of the 3D kinematic model to the 2D silhouette extracted from a monocular image sequence. Next, a Bayesian-based statistical analysis is performed to evaluate the discriminating power of extracted stationary gait features. Through probabilistic simulation, we not only predict the probability of correct recognition (PCR) with regard to different within-class feature variance, but also obtain the upper bound on PCR with regard to different human silhouette resolution. In addition, the maximum number of people in a database is obtained given the allowable error rate. This is extremely important for gait recognition in large databases.
5983751
Fusion of color and infrared video for moving human detection
We approach the task of human silhouette extraction from color and thermal image sequences using automatic image registration. Image registration between color and thermal images is a challenging problem due to the difficulties associated with finding correspondence. However, the moving people in a static scene provide cues to address this problem. In this paper, we propose a hierarchical scheme to automatically find the correspondence between the preliminary human silhouettes extracted from synchronous color and thermal image sequences for image registration. Next, we discuss strategies for probabilistically combining cues from registered color and thermal images for improved human silhouette detection. It is shown that the proposed approach achieves good results for image registration and human silhouette extraction. Experimental results also show a comparison of various sensor fusion strategies and demonstrate the improvement in performance over non-fused cases for human silhouette extraction.
15205125
Fuzzy color histogram and its use in color image retrieval
A conventional color histogram (CCH) considers neither the color similarity across different bins nor the color dissimilarity in the same bin. Therefore, it is sensitive to noisy interference such as illumination changes and quantization errors. Furthermore, CCHs large dimension or histogram bins requires large computation on histogram comparison. To address these concerns, this paper presents a new color histogram representation, called fuzzy color histogram (FCH), by considering the color similarity of each pixel's color associated to all the histogram bins through fuzzy-set membership function. A novel and fast approach for computing the membership values based on fuzzy c-means algorithm is introduced. The proposed FCH is further exploited in the application of image indexing and retrieval. Experimental results clearly show that FCH yields better retrieval results than CCH. Such computing methodology is fairly desirable for image retrieval over large image databases.
9776480
Security Attack Ontology for Web Services
Web services (WS) have become a significant part of the Web because of such attractive features as simple to use, platform independence, and XML/SOAP support. However, these features make WS vulnerable to many new and inherited old security threats. Semantic WS, which are capable of publishing semantic data about their functional and nonfunctional properties, add even more security issues. Now, it becomes easier to attack WS because their semantic data is publicly available. To register and prevent these attacks, especially distributed attacks, new distributed firewalls and intrusion detection systems (F/IDS) have to be applied. However, these F/IDS can be developed by different vendors and they do not have the way to cooperate with each other. This problem can be solved if various F/IDS share a common vocabulary, which can be based on ontologies, to allow them to interact with each other. In this paper, we describe WS security threats and state that they have to be analysed and classified systematically in order to allow the development of better distributed defensive mechanisms for WS using F/IDS. We choose ontologies and OWL/OWL-S over taxonomies because ontologies allow different parties to evolve and share a common understanding of information which can be reasoned and analysed automatically. We develop the security attack ontology for WS and illustrate the benefits of using it with an example.
18870212
Using Dynamic Asynchronous Aggregate Search for Quality Guarantees of Multiple Web Services Compositions
With the increasing impact and popularity of Web service technologies in today's World Wide Web, composition of Web services has received much interest to support enterprise-to-enterprise application integrations. As for service providers and their partners, the Quality of service (QoS) offered by a composite Web service is important. The QoS guarantee for composite services has been investigated in a number of works. However, those works consider only an individual composition or take the viewpoint of a single provider. In this paper, we focus on the problem of QoS guarantees for multiple inter-related compositions and consider the global viewpoints of all providers engaged in the compositions. The contributions of this paper are two folds. We first formalize the problem of QoS guarantees for multi-compositions and show that it can be modelled as a Distributed Constraint Satisfaction Problem (DisCSP). We also take into account the dynamic nature of the Web service environment of which compositions may be formed or dissolved any time. Secondly, we present a dynamic DisCSP algorithm to solve the problem and discuss our initial experiment to show the feasibility of our approach for multiple Web service compositions with QoS guarantees.
18395453
Content-Based Model Template Adaptation and Real-Time System for Behavior Interpretation in Sports Video
In this paper, we present a real-time sports analysis system, which not only recognizes the semantic events, but also concludes the behavior, like player's tactics. To this end, we propose an advanced multiple-player tracking algorithm, which addresses two improvements on practical problems: (1) updating of the player template so that it remains a good model over time, and (2) adaptive scaling of the template size depending on the player motion. In this algorithm, we obtain the initial locations of players in the first frame. The tracking is performed by considering both the kinematic constraints of the player and the color distribution of appearance, thereby achieving promising results. We demonstrate the performance of the proposed system by evaluating it for double tennis matches where the player count and the resulting occlusions are challenging.
2940771
Graph indexing: a frequent structure-based approach
Graph has become increasingly important in modelling complicated structures and schemaless data such as proteins, chemical compounds, and XML documents. Given a graph query, it is desirable to retrieve graphs quickly from a large database via graph-based indices. In this paper, we investigate the issues of indexing graphs and propose a novel solution by applying a graph mining technique. Different from the existing path-based methods, our approach, called gIndex, makes use of frequent substructure as the basic indexing feature. Frequent substructures are ideal candidates since they explore the intrinsic characteristics of the data and are relatively stable to database updates. To reduce the size of index structure, two techniques, size-increasing support constraint and discriminative fragments, are introduced. Our performance study shows that gIndex has 10 times smaller index size, but achieves 3--10 times better performance in comparison with a typical path-based method, GraphGrep. The gIndex approach not only provides and elegant solution to the graph indexing problem, but also demonstrates how database indexing and query processing can benefit form data mining, especially frequent pattern mining. Furthermore, the concepts developed here can be applied to indexing sequences, trees, and other complicated structures as well.
8361551
Composing Security-Aware Software
This article addresses a key issue in security: how to inspire trust by disclosing security properties of software components to others in a component-based software development environment. The authors introduce a component security characterization framework in this endeavor that characterizes security properties by exposing software security profiles to others. The active interface lets software engineers know up front the impact of security properties of a composition's candidate components.