Non-rigid Shape Recognition for Sign Language Understanding
نویسنده
چکیده
The recognition of human activities from video sequences is currently one of the most active areas of research because of its many applications in video surveillance, multimedia communications, medical diagnosis, forensic research and sign language recognition. The work described in this paper describes a new method designed to precisely identify human gestures for Sign Language recognition. The system is to be developed and implemented on a standard personal computer (PC) connected to a colour video camera. The present paper tackles the problem of shape recognition for deformable objects like human hands using modern classification techniques derived from artificial intelligence. Key-Words: Statistical Learning, Shape recognition, Sign-Language
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تاریخ انتشار 2009