• DocumentCode
    2500824
  • Title

    An Ultra-Low-Power Contrast-Based Integrated Camera Node and its Application as a People Counter

  • Author

    Gasparini, Leonardo ; Manduchi, Roberto ; Gottardi, Massimo

  • Author_Institution
    Dept. of Inf. Eng. & Comput. Sci., Univ. of Trento, Povo, Italy
  • fYear
    2010
  • fDate
    Aug. 29 2010-Sept. 1 2010
  • Firstpage
    547
  • Lastpage
    554
  • Abstract
    We describe the implementation in a self-standing system of a novel contrast-based binary CMOS imaging sensor.This sensor is characterized by very low power consumption and wide dynamic range, which makes it attractive for wireless camera network applications. In our implementation,the sensor is interfaced with a Flash-based FPGA processor,which handles data readout and image processing.This self-standing camera node is configured as a system for counting persons walking through a corridor. Simple features are extracted from each image in a video stream at 30 fps. A classifier is designed based on the temporal evolution of these features, which is modeled as a Markov chain. The video stream is then segmented into intervals corresponding to individual persons crossing through the field of view. Experimental results are shown in cross-validated tests over real sequences acquired by the camera.
  • Keywords
    CMOS image sensors; Markov processes; feature extraction; field programmable gate arrays; image segmentation; image sequences; low-power electronics; object detection; Markov chain; binary CMOS imaging sensor; contrast-based integrated camera node; data readout; dynamic range; feature extraction; flash-based FPGA processor; image processing; people counter; self-standing camera node; video segmentation; video stream; wireless camera network; Cameras; Field programmable gate arrays; Image edge detection; Markov processes; Pixel; Radiation detectors; Silicon;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Video and Signal Based Surveillance (AVSS), 2010 Seventh IEEE International Conference on
  • Conference_Location
    Boston, MA
  • Print_ISBN
    978-1-4244-8310-5
  • Type

    conf

  • DOI
    10.1109/AVSS.2010.26
  • Filename
    5597075