HMM-BASED SEGMENTATION AND RECOGNITION OF HUMAN ACTIVITIES FROMA VIDEO SEQUENCES (FriPmPO1)

Author(s) : Feng Niu (University of Miami, United States of America) Mohamed Abdel-Mottaleb (University of Miami, United States of America)

Abstract : Recognizing human activities from image sequences is an active area of research in computer vision. Most of the previous work on activity recognition focuses on recognition from video clips that show only single activities. There are few published algorithms for segmenting and recognizing complex activities that are composed of more than one single activity. In this paper, we present a novel HMM-based approach that uses voting and threshold to automatically and effectively segment and recognize complex activities. Experiments on a database of video clips of different activities show that our method is effective.

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