• DocumentCode
    2996229
  • Title

    Stereo Vision Algorithms for FPGAs

  • Author

    Mattoccia, Stefano

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. of Bologna, Bologna, Italy
  • fYear
    2013
  • fDate
    23-28 June 2013
  • Firstpage
    636
  • Lastpage
    641
  • Abstract
    In recent years, with the advent of cheap and accurate RGBD (RGB plus Depth) active sensors like the Microsoft Kinect and devices based on time-of-flight (ToF) technology, there has been increasing interest in 3D-based applications. At the same time, several effective improvements to passive stereo vision algorithms have been proposed in the literature. Despite these facts and the frequent deployment of stereo vision for many research activities, it is often perceived as a bulky and expensive technology not well suited to consumer applications. In this paper, we will review a subset of state-of-the-art stereo vision algorithms that have the potential to fit a target computing architecture based on low-cost field-programmable gate arrays (FPGAs), without additional external devices (e.g., FIFOs, DDR memories, etc.). Mapping these algorithms into a similar low-power, low-cost architecture would make RGBD sensors based on stereo vision suitable to a wider class of application scenarios currently not addressed by this technology.
  • Keywords
    computer vision; field programmable gate arrays; image sensors; stereo image processing; FPGA; Microsoft Kinect; RGBD active sensor; ToF technology; field programmable gate array; passive stereo vision algorithm; red-green-blue plus depth sensor; time-of-flight technology; Cameras; Computer architecture; Field programmable gate arrays; Optimization; Standards; Stereo vision; 3D; FPGA; dense stereo; matching; stereo vision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on
  • Conference_Location
    Portland, OR
  • Type

    conf

  • DOI
    10.1109/CVPRW.2013.96
  • Filename
    6595940