Abstract
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”.
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© 2012 Springer-Verlag Berlin Heidelberg
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Pande, N., Jain, M., Kapil, D., Guha, P. (2012). The Video Face Book. In: Schoeffmann, K., Merialdo, B., Hauptmann, A.G., Ngo, CW., Andreopoulos, Y., Breiteneder, C. (eds) Advances in Multimedia Modeling. MMM 2012. Lecture Notes in Computer Science, vol 7131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27355-1_46
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DOI: https://doi.org/10.1007/978-3-642-27355-1_46
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