Using audio and video features to classify the most dominant person in a group meeting
Proceedings of the 15th international conference on Multimedia
Automatic objects behaviour recognition from compressed video domain
Image and Vision Computing
Modeling dominance in group conversations using nonverbal activity cues
IEEE Transactions on Audio, Speech, and Language Processing - Special issue on multimodal processing in speech-based interactions
Multimodal recognition of personality traits in human-computer collaborative tasks
Proceedings of the 14th ACM international conference on Multimodal interaction
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MPEG-2 compressed domain information, namely motion vectors and DCT coefficients, is filtered and manipulated to obtain a motion field using a two-dimensional (2-D) translational model. The results are compared to a popular optical flow method, more specifically the one presented by Lucas and Kanade (1981), revealing very good results. Our method provides a very fast motion estimation tool that can be useful for applications where algorithmic cost is critical, such as surveillance systems. All methods are theoretically explained and their efficiency confirmed on real-world data.