• DocumentCode
    254580
  • Title

    3D Hallway Modeling Using a Single Image

  • Author

    Olmschenk, Greg ; Zhigang Zhu

  • Author_Institution
    Grad. Center & the City Coll., City Univ. of New York, New York, NY, USA
  • fYear
    2014
  • fDate
    23-28 June 2014
  • Firstpage
    158
  • Lastpage
    164
  • Abstract
    Real-time, low-resource corridor reconstruction using a single consumer grade RGB camera is a powerful tool for allowing a fast, inexpensive solution to indoor mobility of a visually impaired person or a robot. The perspective and known geometry of a corridor is used to extract the important features of the image and create a 3D model from a single image. Multiple 3D models can be combined to increase confidence and provide a global 3D model. This paper presents our results on 3D corridor modeling using single images. First a simple but effective 3D corridor modeling approach is introduced which makes very few assumptions of the camera information. Second, a perspective based Hough transform algorithm is proposed to detect vertical lines in order to determine the edges of the corridor. Finally, issues in real-time implementation on a smartphone are discussed. Experimental results are provided to validate the proposed approach. This work has the potential to also function in environments with properties analogous to corridors such as highways, sidewalks, city blocks, etc.
  • Keywords
    Hough transforms; feature extraction; image colour analysis; image reconstruction; smart phones; solid modelling; 3D corridor modeling; 3D hallway modeling; consumer grade RGB camera; corridor geometry; feature extraction; low-resource corridor reconstruction; perspective based Hough transform algorithm; red-green-blue camera; robot; smart phone; visually impaired person; Cameras; Feature extraction; Image edge detection; Sensors; Solid modeling; Three-dimensional displays; Transforms; indoor modeling; probabilistic Hough Transform; vanishing point; visual impairment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on
  • Conference_Location
    Columbus, OH
  • Type

    conf

  • DOI
    10.1109/CVPRW.2014.29
  • Filename
    6909974