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Dictionary-Based Face Recognition from Video

  • Yi-Chen Chen
  • Vishal M. Patel
  • P. Jonathon Phillips
  • Rama Chellappa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7577)

Abstract

The main challenge in recognizing faces in video is effectively exploiting the multiple frames of a face and the accompanying dynamic signature. One prominent method is based on extracting joint appearance and behavioral features. A second method models a person by temporal correlations of features in a video. Our approach introduces the concept of video-dictionaries for face recognition, which generalizes the work in sparse representation and dictionaries for faces in still images. Video-dictionaries are designed to implicitly encode temporal, pose, and illumination information. We demonstrate our method on the Face and Ocular Challenge Series (FOCS) Video Challenge, which consists of unconstrained video sequences. We show that our method is efficient and performs significantly better than many competitive video-based face recognition algorithms.

Keywords

Receiver Operating Characteristic Curve Face Recognition Video Sequence Face Image False Acceptance Rate 
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

  • Yi-Chen Chen
    • 1
  • Vishal M. Patel
    • 1
  • P. Jonathon Phillips
    • 2
  • Rama Chellappa
    • 1
  1. 1.Department of Electrical and Computer Engineering, Center for Automation ResearchUniversity of MarylandCollege ParkUSA
  2. 2.National Institute of Standards and TechnologyGaithersburgUSA

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