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FaceTrack - Face Detection & Tracking in Compressed Video


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(to be updated soon)

Human activities in videos provides direct information about the video content. Summaries of people appearance in the spatial and temporal dimensions can help users to quickly understand the interaction among people. Example questions answered are who are in the video, in what order, who has face-to-face discussion with whom. We are developing algorithms and systems for real-time detection, accurate tracking, and effective summarization of human faces in the video compressed domain. The real-time detection component uses the MPEG compressed data to detect face objects and refine the results by tracking the movement of faces. Various motion models in Kalman filters have been studied for tracking. In specific domains (e.g., interview videos), high-level transition models are also explored to model the probabilistic transition patterns among speakers. The same detection-tracking-transition paradigm can be applied to other domains (e.g., sports, presentation) for understanding the high-level content of videos.

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Last updated: June 12, 2002.