Interactive Object Recognition through Hypothesis Generation and Confirmation Interactive Object Recognition through Hypothesis Generation and Confirmation

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Author(s)

    • KURNIA Rahmadi
    • Department of Information and Computer Sciences, Saitama University
    • NAKAMURA Akio
    • Department of Machinery System Engineering, Tokyo Denki University
    • KUNO Yoshinori
    • Department of Information and Computer Sciences, Saitama University

Abstract

copyright(c)2006 IEICE許諾番号:08RB0010総務省戦略的情報通信研究開発推進制度(SCOPE) 特定領域重点型研究開発 次世代ヒューマンインタフェース・コンテンツ技術視覚情報に基づく人間とロボットの対面およびネットワークコミュニケーション(051303007)平成17年度〜平成19年度 総務省戦略的情報通信研究開発推進制度(SCOPE)研究成果報告書 Strategic Information and Communications R&D Promotion Programme(SCOPE)Ministry of Internal Affairs and CommunicationsHuman-Robot Communication through Visual Information in Face-to-Face and Network Modes(051303007)2005-2007Final Project Report平成20年3月研究代表者 久野義徳(埼玉大学大学院理工学研究科教授)

An effective human-robot interaction is essential for wide penetration of service robots into the market. Such robot needs a vision system to recognize objects. It is, however, difficult to realize vision systems that can work in various conditions. More robust techniques of object recognition and image segmentation are essential. Thus, we have proposed to use the human user's assistance for objects recognition through speech. This paper presents a system that recognizes objects in occlusion and/or multicolor cases using geometric and photometric analysis of images. Based on the analysis results, the system makes a hypothesis of the scene. Then, it asks the user for confirmation by describing the hypothesis. If the hypothesis is not correct, the system generates another hypothesis until it correctly understands the scene. Through experiments on a real mobile robot, we have confirmed the usefulness of the system.

Journal

  • IEICE Transactions on Information and Systems, D

    IEICE Transactions on Information and Systems, D 89(7), 2197-2206, 2006-07-01

    The Institute of Electronics, Information and Communication Engineers

References:  18

Cited by:  4

Codes

  • NII Article ID (NAID)
    110007541109
  • NII NACSIS-CAT ID (NCID)
    AA10826272
  • Text Lang
    ENG
  • Article Type
    Journal Article
  • ISSN
    09168532
  • Data Source
    CJP  CJPref  NII-ELS  IR 
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