Recognizing human motions from surrounding viewpoints employing hierarchical eigenspaces

The development of an automatic human motion recognition system leads to the solution to the problems concerning the video-based applications in recognizing human activities. Such a system is to be investigated in the context of human motion analysis. Although there were a large number of researches in this area for a long time, there was little attention given to the development of a structured database for successful retrieval of motion data incorporating the time-space trade-off. We have proposed a system which is capable of dealing with large set of motion data employing an efficient database structure with improved performance. We have analyzed two motion representation techniques to realize the effectiveness of the system. Performance evaluation is performed by synthesized 3D human motions observed from eight camera directions. Finally, our results show that the proposed recognition scheme performs well for the captured motions.