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Invariant Surface-Based Shape Descriptor for Dynamic Surface Encoding

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Computer Vision – ACCV 2012 (ACCV 2012)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7724))

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Abstract

This paper presents a novel approach to represent spatio-temporal visual information. We introduce a surface-based shape model whose structure is invariant to surface variations over time to describe 3D dynamic surfaces (e.g., obtained from multiview video capture). The descriptor is defined as a graph lying on object surfaces and anchored to invariant local features (e.g., extremal points). Geodesic-consistency-based priors are used as cues within a probabilistic framework to maintain the graph invariant, even though the surfaces undergo non-rigid deformations. Our contribution brings to 3D geometric data a temporally invariant structure that relies only on intrinsic surface properties, and is independent of surface parameterization (i.e., surface mesh connectivity). The proposed descriptor can therefore be used for efficient dynamic surface encoding, through transformation into 2D (geometry) images, as its structure can provide an invariant representation for 3D mesh models. Various experiments on challenging publicly available datasets are performed to assess invariant property and performance of the descriptor.

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Author information

Authors and Affiliations

  1. Graduate School of Informatics, Kyoto University, Japan

    Tony Tung & Takashi Matsuyama

Authors
  1. Tony Tung
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  2. Takashi Matsuyama
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, 151-744, Gwanak-gu, Seoul, Korea

    Kyoung Mu Lee

  2. Microsoft Research Asia, No. 5, Danling st., Haidian district, 100080, Beijing, P.R. China

    Yasuyuki Matsushita

  3. School of Interactive Computing, Georgia Institute of Technology, 801 Atlantic Drive, CCB 315, 30332, Atlanta, GA, USA

    James M. Rehg

  4. Institute of Automation, National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Zhong Quan Cun East Road 95, Haidian District, 100 190, Beijing, P.R. China

    Zhanyi Hu

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Tung, T., Matsuyama, T. (2013). Invariant Surface-Based Shape Descriptor for Dynamic Surface Encoding. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds) Computer Vision – ACCV 2012. ACCV 2012. Lecture Notes in Computer Science, vol 7724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37331-2_37

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  • DOI: https://doi.org/10.1007/978-3-642-37331-2_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37330-5

  • Online ISBN: 978-3-642-37331-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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