• DocumentCode
    3459239
  • Title

    Instant segmentation and feature extraction for recognition of simple objects on mobile phones

  • Author

    Hartl, Andreas ; Arth, Clemens ; Schmalstieg, Dieter

  • Author_Institution
    Inst. for Comput. Graphics & Vision, Graz Univ. of Technol., Graz, Austria
  • fYear
    2010
  • fDate
    13-18 June 2010
  • Firstpage
    17
  • Lastpage
    24
  • Abstract
    Object detection and recognition algorithms are an integral part of the architecture of many modern image processing systems employing Computer Vision (CV) techniques. In this paper we describe our work in the area of segmentation and recognition of simple objects in mobile phone imagery. Given an image of several objects on a structured background, we show how these objects can be segmented efficiently and how features can be extracted efficiently for further object recognition and classification. We prove the algorithms presented are useful given a set of test cases, and we show that the algorithms discussed can be used for instant object segmentation and recognition in a real-world application on ordinary off-the-shelf smartphones.
  • Keywords
    feature extraction; image segmentation; mobile handsets; object detection; object recognition; computer vision techniques; feature extraction; mobile phones; object detection; object recognition; object segmentation; off-the-shelf smartphones; Computer architecture; Computer vision; Feature extraction; Image processing; Image recognition; Image segmentation; Mobile handsets; Object detection; Object recognition; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    2160-7508
  • Print_ISBN
    978-1-4244-7029-7
  • Type

    conf

  • DOI
    10.1109/CVPRW.2010.5543245
  • Filename
    5543245