The Video Face Book

  • Nipun Pande
  • Mayank Jain
  • Dhawal Kapil
  • Prithwijit Guha
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7131)


Videos are often characterized by the human participants, who in turn, are identified by their faces. We present a completely unsupervised system to index videos through faces. A multiple face detector-tracker combination bound by a reasoning scheme and operational in both forward and backward directions is used to extract face tracks from individual shots of a shot segmented video. These face tracks collectively form a face log which is filtered further to remove outliers or non-face regions. The face instances from the face log are clustered using a GMM variant to capture the facial appearance modes of different people. A face Track-Cluster-Correspondence-Matrix (TCCM) is formed further to identify the equivalent face tracks. The face track equivalences are analyzed to identify the shot presences of a particular person, thereby indexing the video in terms of faces, which we call the “Video Face Book”.


Face Detection Face Region Color Distribution Face Track Cluster Purity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Nipun Pande
    • 1
  • Mayank Jain
    • 1
  • Dhawal Kapil
    • 1
  • Prithwijit Guha
    • 1
  1. 1.TCS Innovation LabsNew DelhiIndia

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