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Hand-Object Sense: A Hand-held Object Recognition System Based on RGB-D Information

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Published:13 October 2015Publication History

ABSTRACT

Hand-held objects play an important role in human-human and human-machine interaction. It can be used as a reference for understanding user intentions or user requirements. In this technical demonstration, we introduce an object recognition system called Hand-Object Sense that can automatically recognize the object held by user. This system first detects and segments the hand-held object by exploiting skeleton information combined with depth information. Second, in the object recognition stage, this system exploits features computed in different ways and fuses them to improve the recognition accuracy. Our system can recognize objects in real-time and have a good tolerance to angle and scale transformation. Furthermore, it has a good generalization capability for unknown objects.

References

  1. Xiong Lv, Shuqiang Jiang, Luis Herranz, and Shuang Wang. Rgb-d hand-held object recognition based on heterogeneous feature fusion. Journal of Computer Science and Technology, 30(2):340--352, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  2. Shuang Wang and Shuqiang Jiang. Instre: A new benchmark for instance-level object retrieval and recognition. ACM Trans. Multimedia Comput. Commun. Appl., 11(3):37:1--37:21, February 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Hand-Object Sense: A Hand-held Object Recognition System Based on RGB-D Information

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    • Published in

      cover image ACM Conferences
      MM '15: Proceedings of the 23rd ACM international conference on Multimedia
      October 2015
      1402 pages
      ISBN:9781450334594
      DOI:10.1145/2733373

      Copyright © 2015 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 13 October 2015

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      • demonstration

      Acceptance Rates

      MM '15 Paper Acceptance Rate56of252submissions,22%Overall Acceptance Rate995of4,171submissions,24%

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      October 28 - November 1, 2024
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