Carnegie Mellon University
Automatic Clustering of Faces in Meetings

Carlos Vallespi-Gonzalez , Fernando De la Torre Frade, Manuela Veloso , and Takeo Kanade
ICIP 2006, October, 2006, pp. 1841-1844.

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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, and a temporal subspace clustering algorithm. The effectiveness and robustness of the proposed system is demonstrated over a data set of long videos (i.e. 1 hour).

Face Detection, Face tracking, clustering, subspace methods, meeting understanding

Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Associated Lab(s) / Group(s): People Image Analysis Consortium and MultiRobot Lab
Associated Project(s): Camera Assisted Meeting Event Observer
Number of pages: 4

Text Reference
Carlos Vallespi-Gonzalez , Fernando De la Torre Frade, Manuela Veloso , and Takeo Kanade, "Automatic Clustering of Faces in Meetings," ICIP 2006, October, 2006, pp. 1841-1844.

BibTeX Reference
   author = "Carlos {Vallespi-Gonzalez } and Fernando {De la Torre Frade} and Manuela {Veloso } and Takeo Kanade",
   title = "Automatic Clustering of Faces in Meetings",
   booktitle = "ICIP 2006",
   pages = "1841-1844",
   month = "October",
   year = "2006",