• DocumentCode
    2765774
  • Title

    Indoor signage detection based on saliency map and bipartite graph matching

  • Author

    Wang, Shuihua ; Tian, YingLi

  • Author_Institution
    Dept. of Electr. Eng., City Coll. of New York, New York, NY, USA
  • fYear
    2011
  • fDate
    12-15 Nov. 2011
  • Firstpage
    518
  • Lastpage
    525
  • Abstract
    Object detection plays a very important role in many applications such as image retrieval, surveillance, robot navigation, wayfinding, etc. In this paper, we propose a novel approach to detect indoor signage to help blind people find their destinations in unfamiliar environments. Our method first extracts the attended areas by using a saliency map. Then the signage is detected in the attended areas by using bipartite graph matching. The proposed method can handle multiple signage detection. Experimental results on our collected indoor signage dataset demonstrate the effectiveness and efficiency of our proposed method. Furthermore, saliency maps could eliminate the interference information and improve the accuracy of the detection results.
  • Keywords
    handicapped aids; medical computing; object detection; bipartite graph matching; blind people; indoor signage detection; multiple signage detection; object detection; saliency map; Bipartite graph; Cameras; Computational efficiency; Elevators; Feature extraction; Image color analysis; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine Workshops (BIBMW), 2011 IEEE International Conference on
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    978-1-4577-1612-6
  • Type

    conf

  • DOI
    10.1109/BIBMW.2011.6112422
  • Filename
    6112422