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Asian Conference on Computer Vision

ACCV 2014: Computer Vision -- ACCV 2014 pp 626–641Cite as

Spatiotemporal Derivative Pattern: A Dynamic Texture Descriptor for Video Matching

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9007))

Abstract

We present Spatiotemporal Derivative Pattern (SDP), a descriptor for dynamic textures. Using local continuous circular and spiral neighborhoods within video segments, SDP encodes the derivatives of the directional spatiotemporal patterns into a binary code. The main strength of SDP is that it uses fewer frames per segment to extract more distinctive features for efficient representation and accurate classification of the dynamic textures. The proposed SDP is tested on the Honda/UCSD and the YouTube face databases for video based face recognition and on the Dynamic Texture database for dynamic texture classification. Comparisons with existing state-of-the-art methods show that the proposed SDP achieves the overall best performance on all three databases. To the best of our knowledge, our algorithm achieves the highest results reported to date on the challenging YouTube face database.

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Author information

Authors and Affiliations

  1. Electrical Engineering Department, Tafresh University, Tafresh, Iran

    Farshid Hajati, Mohammad Tavakolian & Soheila Gheisari

  2. Electrical Engineering Department, Central Tehran Branch, Islamic Azad University, Tehran, Iran

    Soheila Gheisari

  3. Computer Science and Software Engineering, The University of Western Australia, Crawley, WA, 6009, Australia

    Ajmal Saeed Mian

Authors
  1. Farshid Hajati
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  2. Mohammad Tavakolian
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  3. Soheila Gheisari
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  4. Ajmal Saeed Mian
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Corresponding author

Correspondence to Farshid Hajati .

Editor information

Editors and Affiliations

  1. Technische Universität München, Garching, Germany

    Daniel Cremers

  2. University of Adelaide, Adelaide, South Australia, Australia

    Ian Reid

  3. Keio University, Yokohama, Kanagawa, Japan

    Hideo Saito

  4. University of California at Merced, Merced, California, USA

    Ming-Hsuan Yang

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Hajati, F., Tavakolian, M., Gheisari, S., Mian, A.S. (2015). Spatiotemporal Derivative Pattern: A Dynamic Texture Descriptor for Video Matching. In: Cremers, D., Reid, I., Saito, H., Yang, MH. (eds) Computer Vision -- ACCV 2014. ACCV 2014. Lecture Notes in Computer Science(), vol 9007. Springer, Cham. https://doi.org/10.1007/978-3-319-16814-2_41

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  • DOI: https://doi.org/10.1007/978-3-319-16814-2_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16813-5

  • Online ISBN: 978-3-319-16814-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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