Abstract Human recognition and movement analysis are important tasks in various applications especially in video surveillance. This paper proposes a multi agent architecture for sensor based automated scene surveillance using Microsoft Kinecet camera. It aims to record videos about each person that appears in the scene and to generate sonorous alarms when an abnormal situation is deduced. This decision making support... Human recognition and movement analysis are important tasks in various applications especially in video surveillance. This paper proposes a multi agent architecture for sensor based automated scene surveillance using Microsoft Kinecet camera. It aims to record videos about each person that appears in the scene and to generate sonorous alarms when an abnormal situation is deduced. This decision making support system had to deal with environment uncertainties through fuzzy expert system which is responsible of person recognition. Read More Read Less

Abstract The increase in CPU power and screen quality of todays smartphones as well as the availability of high bandwidth wireless networks has enabled high quality mobile videoconferencing never seen before. However, adapting to the variety of devices and network conditions that come as a result is still not a trivial issue. In this paper, we present a multiple participant videoconferencing... The increase in CPU power and screen quality of todays smartphones as well as the availability of high bandwidth wireless networks has enabled high quality mobile videoconferencing never seen before. However, adapting to the variety of devices and network conditions that come as a result is still not a trivial issue. In this paper, we present a multiple participant videoconferencing service that adapts to different kind of devices and access networks while providing an stable communication. By combining network quality detection and the use of a multipoint control unit for video mixing and transcoding, desktop, tablet and mobile clients can participate seamlessly. We also describe the cost in terms of bandwidth and CPU usage of this approach in a variety of scenarios. Read More Read Less

Abstract This paper considered performance of content based image retrieval system using image representation nonparametric algorithms. Performance comparison of Epanechnikov, Gaussian and Histogram non-parametric algorithms was done in a generic image retrieval system. Chan & Vese and Cosine Angle Distance algorithms were used for segmentation and similarity matching respectively. The performance of the non-parametric techniques was measured using recall-precision curve and... This paper considered performance of content based image retrieval system using image representation nonparametric algorithms. Performance comparison of Epanechnikov, Gaussian and Histogram non-parametric algorithms was done in a generic image retrieval system. Chan & Vese and Cosine Angle Distance algorithms were used for segmentation and similarity matching respectively. The performance of the non-parametric techniques was measured using recall-precision curve and the Bull’s Eye performance score. The experimental results showed that estimating techniques performed better than the absolute value technique. The study then looked at the limitations of these techniques. Read More Read Less