Task Specific Factors for Video Characterization

  • Ranjeeth Kumar
  • S. Manikandan
  • C. V. Jawahar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4338)


Factorization methods are used extensively in computer vision for a wide variety of tasks. Existing factorization techniques extract factors that meet requirements such as compact representation, interpretability, efficiency, dimensionality reduction etc. However, when the extracted factors lack interpretability and are large in number, identification of factors that cause the data to exhibit certain properties of interest is useful in solving a variety of problems. Identification of such factors or factor selection has interesting applications in data synthesis and recognition. In this paper simple and efficient methods are proposed, for identification of factors of interest from a pool of factors obtained by decomposing videos represented as tensors into their constituent low rank factors. The method is used to select factors that enable appearance based facial expression transfer and facial expression recognition. Experimental results demonstrate that the factor selection facilitates efficient solutions to these problems with promising results.


Facial Expression Singular Value Decomposition Basis Image Expression Recognition Facial Expression Recognition 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ranjeeth Kumar
    • 1
  • S. Manikandan
    • 1
  • C. V. Jawahar
    • 1
  1. 1.Center for Visual Information TechnologyInternational Institute of Information TechnologyHyderabadIndia

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