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Human tracking in video sequences and human activities recognition are important tasks with multiple applications in video surveillance, human computer interacion, sports analysis, etc.

An important and active interdisciplinary research area deals with the development of computational systems capable of automatically interpret a video sequence and extract an useful and close to natural language information.

The main aim of this project is to develop models, algorithms and intelligent systems for automatic human activity recognition in surveillance environments.

The hypothesis can be formulated as follows: “The combination of visual tracking methods, pattern recognition methods and learning methods can produce effective and efficient automatic human activity recognition systems”. Involved people are expertise in image processing, computer vision, pattern recognition, heuristic optimization and software development . More specifically, they have a solid experience in the development of video based visual tracking algorithms.

 
 

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