posted on 2006-01-01, 00:00authored byCarlos Vallespi, Fernando De la Torre, Manuela Veloso, Takeo Kanade
Meetings are an integral part of business life for any organization.
In previous work, we have developed a physical
awareness system called CAMEO (Camera Assisted Meeting
Event Observer) to record and process the audio/visual information
of a meeting. An important task in meeting understanding
is to know who and how many people are attending
the meeting. In this paper, we present an automatic approach
to detect, track, and cluster people’s faces in long video sequences.
This is a challenging problem due to the appearance
variability of people’s faces (illumination, expression, pose,
...). Two main novelties are presented:
• A robust real-time adaptive subspace face tracker which
combines color and appearance.
• A temporal subspace clustering algorithm.
The effectiveness and robustness of the proposed system