Feature point extraction using scale-space representation

An algorithm for feature point extraction is presented. It is based on a scale-space representation of the image as well as a system for tracking across scales. Using synthetic and real images, it is shown that the proposed algorithm produces stable and well-localized feature points estimates two essential properties for video applications

Fusion of Face and Speech Data for Person Identity Verification

Multi-modal person identity authentication is gaining more and more attention in the biometrics area. Combining different modalities increases the performance and robustness of identity authentication systems. The authentication problem is a binary classification problem. The fusion of different modalities can be therefore performed by binary classifiers. We propose to evaluate different binary classification schemes (SVM, MLP, C4.5, Fisher's linear discriminant, Bayesian classifier) on a large database (295 subjects) containing audio and video data. The identity authentication is based on two modalities: face and speec

Universal multimedia access from wired and wireless systems

Personal computing and communication devices such as computers, personal digital assistants (PDAs), and mobile phones are moving to their next generation in which the end user will be able to access a multitude of information with a single device either locally or through a network. One likely trend in future personal computing and personal communication is that there will not be a single but several equivalent devices available to users allowing access to information in various forms. Each user, depending on his/her needs would access one or several among them depending on the situation and his/her preference. Using existing protocol mechanisms, in this case, a mapping and negotiation of resources during connection setup would be performed, which would remain in place throughout the life of the connection. This paper provides an overview of universal multimedia access (UMA), a concept for accessing multimedia content through a variety of possible schemes, and discusses some of the issues that arise regarding its deployment. In particular, UMA will provide a solution for adapting the delivered content when users attempt to access their choice irrespective of their terminal characteristics and communication infrastructure, as apposed to the assumption that the content remains fixed and the objective is to deliver the original content at all times. This recognition represents the impetus for the development of media descriptions and hence UMA; that is, the notion that valuable information can be derived from a variety of conversions of a multimedia content source. The issues discussed are future requirements on content servers and multimedia viewers, media conversions, UMA protocols, and UMA network architectures. The problems addressed are quality of service issues in network solutions for multimedia communications and reconfigurable architectures and network control based on source adaptations through media conversions and transcoding

Privacy Enabling Technology for Video Surveillance

In this paper, we address the problem privacy in video surveillance. We propose an efficient solution based on transform-domain scrambling of regions of interest in a video sequence. More specifically, the sign of selected transform coefficients is flipped during encoding. We address more specifically the case of Motion JPEG 2000. Simulation results show that the technique can be successfully applied to conceal information in regions of interest in the scene while providing with a good level of security. Furthermore, the scrambling is flexible and allows adjusting the amount of distortion introduced. This is achieved with a small impact on coding performance and negligible computational complexity increase. In the proposed video surveillance system, heterogeneous clients can remotely access the system through the Internet or 2G/3G mobile phone network. Thanks to the inherently scalable Motion JPEG 2000 codestream, the server is able to adapt the resolution and bandwidth of the delivered video depending on the usage environment of the client

Feature point tracking combining the Interacting Multiple Model filter and an efficient assignment algorithm

An algorithm for feature point tracking is proposed. The Interacting Multiple Model (IMM) filter is used to estimate the state of a feature point. The problem of data association, i.e. establishing which feature point to use in the state estimator, is solved by an assignment algorithm. A track management method is also developed. In particular a track continuation method and a track quality indicator are presented. The evaluation of the tracking system on real sequences shows that the IMM filter combined with the assignment algorithm outperforms the Kalman filter, used with the Nearest Neighbour (NN) filter, in terms of data association performance and robustness to sudden feature point manoeuvre