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Face Retrieval in Broadcasting News Video by Fusing Temporal and Intensity Information

  • Duy-Dinh Le
  • Shin’ichi Satoh
  • Michael E. Houle
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4071)

Abstract

Human faces play an important role in efficiently indexing and accessing video contents, especially broadcasting news video. However, face appearance in real environments exhibits many variations such as pose changes, facial expressions, aging, illumination changes, low resolution and occlusion, making it difficult for current state of the art face recognition techniques to obtain reasonable retrieval results. To handle this problem, this paper proposes an efficient retrieval method by integrating temporal information into facial intensity information. First, representative faces are quickly generated by using facial intensities to organize the face dataset into clusters. Next, temporal information is introduced to reorganize cluster memberships so as to improve overall retrieval performance. For scalability and efficiency, the clustering is based on a recently-proposed model involving correlations among relevant sets (neighborhoods) of data items. Neighborhood queries are handled using an approximate search index. Experiments on the 2005 TRECVID dataset show promising results.

Keywords

Face Recognition Temporal Information Face Appearance News Video Cluster Candidate 
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 2006

Authors and Affiliations

  • Duy-Dinh Le
    • 1
  • Shin’ichi Satoh
    • 1
    • 2
  • Michael E. Houle
    • 2
  1. 1.Department of InformaticsThe Graduate University for Advanced StudiesTokyoJapan
  2. 2.National Institute of InformaticsTokyoJapan

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