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IAPR Workshop on Multimodal Pattern Recognition of Social Signals in Human-Computer Interaction

MPRSS 2014: Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction pp 3–14Cite as

Automatic Image Collection of Objects with Similar Function by Learning Human Grasping Forms

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8869))

Abstract

This paper proposes an automatic functional object segmentation method based on modeling the relationship between grasping hand form and the object appearance. First the relationship among a representative grasping pattern and a position and pose of a object relative to the hand is learned based on a few typical functional objects. By learning local features from the hand grasping various tools with various way to hold them, the proposed method can estimate the position, scale, direction of the hand and the region of the grasped object. By some experiments, we demonstrate that the proposed method can detect them in cluttered backgrounds.

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Author information

Authors and Affiliations

  1. Ritsumeikan University, Shiga, Japan

    Shinya Morioka, Tadashi Matsuo, Yasuhiro Hiramoto, Nobutaka Shimada & Yoshiaki Shirai

Authors
  1. Shinya Morioka
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  2. Tadashi Matsuo
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  3. Yasuhiro Hiramoto
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  4. Nobutaka Shimada
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  5. Yoshiaki Shirai
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Corresponding author

Correspondence to Tadashi Matsuo .

Editor information

Editors and Affiliations

  1. University of Ulm, Universität Ulm, Ulm, Germany

    Friedhelm Schwenker

  2. University of Southern California, Playa Vista, California, USA

    Stefan Scherer

  3. University of Southern California, Playa Vista, California, USA

    Louis-Philippe Morency

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© 2015 Springer International Publishing Switzerland

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Morioka, S., Matsuo, T., Hiramoto, Y., Shimada, N., Shirai, Y. (2015). Automatic Image Collection of Objects with Similar Function by Learning Human Grasping Forms. In: Schwenker, F., Scherer, S., Morency, LP. (eds) Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction. MPRSS 2014. Lecture Notes in Computer Science(), vol 8869. Springer, Cham. https://doi.org/10.1007/978-3-319-14899-1_1

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  • DOI: https://doi.org/10.1007/978-3-319-14899-1_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14898-4

  • Online ISBN: 978-3-319-14899-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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