Human Activity Detection And Recognition

Human activity detection and recognition

Faculty: Jianbo Shi

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We are developing computer algorithms to recognize human at multiple levels of abstractions: from the basic body limb tracking, to human identification, to gesture recognition, to activity inference. The ultimate goal is to develop computation algorithms to understand human behavior in video.

The rapid growth in size of storage devices allows us to store hours, days or even months of video data. Watching through and analyzing videos of such length is no longer feasible. In order to summarize or index videos (for search purposes) we need to develop algorithms which detect and classify events happening in the video without human supervision. To identify and describe various types of events we seek important features and ways of extracting/learning them from the video data.