| Summary: | 碩士 === 國立臺灣大學 === 電機工程學研究所 === 93 === Recognition of human activities has become an interesting research topic in computer vision, with a wide range of applications in virtual reality, surveillance systems, human-computer interface, human motion analysis and multimedia compression, etc. Recognition of human activities mainly involves two aspects: acquirement of human motion information and representation of human activities. The difficulties of human information acquirement are to extract human body information and characteristics from the image sequence. The challenge of human activities representation is how to utilize human information to recognize complex and varied human actions.
This thesis focuses on the representation of human activities. A human action recognition system for home-care is presented. The methodology of recognition system depends on the intuitional identification of human to design individual rules for each action. According to the correlation between rules and human information, actions can be recognized. This system extracts the human body information from the image sequence which is generated by a 3D human body animation software. Fuzzy set theory is utilized to derive the weighting of each action. By comparing the weighting of each action, the action with the largest weighting is chosen as the output of this recognition system. According to a series of experiments, the comparison between 3D human animation and program results shows that the proposed system can recognize human actions successfully.
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