Affordance-based 3D feature for generic object recognition

M. Iizuka, S. Akizuki, M. Hashimoto

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Techniques for generic object recognition, which targets everyday objects such as cups and spoons, and techniques for approach vector estimation (e.g. estimating grasp position), which are needed for carrying out tasks involving everyday objects, are considered necessary for the perceptual system of service robots. In this research, we design feature for generic object recognition so they can also be applied to approach vector estimation. To carry out tasks involving everyday objects, estimating the function of the target object is critical. Also, as the function of holding liquid is found in all cups, so a function is shared in each type (class) of everyday objects. We thus propose a generic object recognition method that can estimate the approach vector by expressing an object's function as feature. In a test of the generic object recognition of everyday objects, we confirmed that our proposed method had a 92% recognition rate. This rate was 11% higher than the mainstream generic object recognition technique of using convolutional neural network (CNN).

    Original languageEnglish
    Title of host publicationThirteenth International Conference on Quality Control by Artificial Vision 2017
    EditorsAtsushi Yamashita, Hajime Nagahara, Kazunori Umeda
    PublisherSPIE
    ISBN (Electronic)9781510611214
    DOIs
    Publication statusPublished - 2017
    Event13th International Conference on Quality Control by Artificial Vision, QCAV 2017 - Tokyo, Japan
    Duration: 2017 May 142017 May 16

    Publication series

    NameProceedings of SPIE - The International Society for Optical Engineering
    Volume10338
    ISSN (Print)0277-786X
    ISSN (Electronic)1996-756X

    Other

    Other13th International Conference on Quality Control by Artificial Vision, QCAV 2017
    Country/TerritoryJapan
    CityTokyo
    Period17/5/1417/5/16

    Keywords

    • Affordance
    • Generic object recognition

    ASJC Scopus subject areas

    • Electronic, Optical and Magnetic Materials
    • Condensed Matter Physics
    • Computer Science Applications
    • Applied Mathematics
    • Electrical and Electronic Engineering

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