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Summary
(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.
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