Audio-visual analysis for event understanding
AMC '09 Proceedings of the 2009 workshop on Ambient media computing
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
IEEE Transactions on Image Processing
A new shot change detection method using information from motion estimation
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Human behavior classification by analyzing periodic motions
Frontiers of Computer Science in China
Spatiotemporal analysis of human activities for biometric authentication
Computer Vision and Image Understanding
A new heat-map-based algorithm for human group activity recognition
Proceedings of the 20th ACM international conference on Multimedia
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This paper presents a novel approach for automatic recognition of human activities for video surveillance applications. We propose to represent an activity by a combination of category components and demonstrate that this approach offers flexibility to add new activities to the system and an ability to deal with the problem of building models for activities lacking training data. For improving the recognition accuracy, a confident-frame-based recognition algorithm is also proposed, where the video frames with high confidence for recognizing an activity are used as a specialized local model to help classify the remainder of the video frames. Experimental results show the effectiveness of the proposed approach.