• DocumentCode
    3673987
  • Title

    Retrieving gray-level information from a Binary Sensor and its application to gesture detection

  • Author

    Orazio Gallo;Iuri Frosio;Leonardo Gasparini;Kari Pulli;Massimo Gottardi

  • Author_Institution
    NVIDIA, Santa Clara, California, United States
  • fYear
    2015
  • fDate
    6/1/2015 12:00:00 AM
  • Firstpage
    21
  • Lastpage
    26
  • Abstract
    We report on the use of a CMOS Contrast-based Binary Vision Sensor (CBVS), with embedded contrast extraction, for gesture detection applications. The first advantage of using this sensor over commercial imagers is a dynamic range of 120dB, made possible by a pixel design that effectively performs auto-exposure control. Another benefit is that, by only delivering the pixels detecting a contrast, the sensor requires a very limited bandwidth. We leverage the sensor´s fast 150μs readout speed, to perform multiple reads during a single exposure; this allows us to estimate gray-level information from the otherwise binary pixels. As a use case for this novel readout strategy, we selected in-car gesture detection, for which we carried out preliminary tests showing encouraging results.
  • Keywords
    "Power demand","Kernel","Lighting","Dynamic range","IP networks","Training","Data mining"
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops (CVPRW), 2015 IEEE Conference on
  • Electronic_ISBN
    2160-7516
  • Type

    conf

  • DOI
    10.1109/CVPRW.2015.7301362
  • Filename
    7301362