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A Computationally Efficient Algorithm for Large Scale Near-Duplicate Video Detection

  • Dawei Liu
  • Zhihua Yu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8936)

Abstract

Large scale near-duplicate video detection is very desirable for web video processing, especially the computational efficiency is essential for practical applications. In this paper, we present a computationally efficient algorithm based on multi-layer video content analysis. Local features are extracted from key frames of videos and indexed by an novel adaptive locality sensitive hashing scheme. By learning several parameters, fast retrieval in the new hashing structure is performed without high dimensional distance computations and achieves better real-time retrieving performance compared with other state-of-the-art approaches. Then a descriptor filtering method and a two-level matching scheme is performed to generate a relevance score for detection. Experiments on near-duplicate video detection tasks including various transformed videos demonstrate the efficiency gains of the proposed algorithm.

Keywords

Near-duplicate Detection Locality sensitive hashing SURF Multimedia content analysis 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Dawei Liu
    • 1
  • Zhihua Yu
    • 1
    • 2
  1. 1.Instititue of Network Technology, Institute of Computing Technology(Yantai)CASShandongP.R. China
  2. 2.Instititue of Computing TechnologyCASBeijingP.R. China

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