• DocumentCode
    187398
  • Title

    A single sensor NIR depth camera for gesture control

  • Author

    Ionescu, Daniela ; Suse, Viorel ; Gadea, Cristian ; Solomon, Bogdan ; Ionescu, Bogdan ; Islam, Shariful ; Cordea, Marius

  • Author_Institution
    Sch. of Electr. Eng. & Comput. Sci., Univ. of Ottawa, Ottawa, ON, Canada
  • fYear
    2014
  • fDate
    12-15 May 2014
  • Firstpage
    1600
  • Lastpage
    1605
  • Abstract
    There is a large amount of sustained research activity in the area of Human-Computer Interaction (HCI). Gesture control is one of hottest in this field. Although gesture control research began with terminals attached to computers in combination with a pointing device, the large scale implementation and utilization of gesture control continues to be infeasible today. As machine vision, image processing, and artificial intelligence algorithms are error prone, gestures will never be interpreted in the same way for all instances of the gesture´s appearance, especially due to changes of the ambient light. This latter condition led to the use of near infrared (NIR) illumination such that the recorded scene is not affected by light variations. Since the posture of a gesture may require the processing of overlapping features, reliability is greatly improved through the use of images that contain a third dimension. In this paper, a smart and real-time depth camera based on a new depth generation principle is introduced. A monotonic increasing and decreasing function is used to control the frequency and duty-cycle of the NIR illumination pulses. The adjusted light pulses reflect off of the object of interest and are captured as a series of images. A reconfigurable hardware architecture calculates the depth-map of the visible face of the object in real-time from a number of images. The final depth map is then used for gesture detection, tracking and recognition. A series of tests and measurements will explain how the camera builds the depth map and how it can operate in both near and far ranges. Results on controlling video game consoles and Smart TVs using the above camera will be given.
  • Keywords
    cameras; frequency control; gesture recognition; infrared detectors; infrared imaging; lighting; sampled data systems; HCI; NIR illumination pulse control; artificial intelligence algorithm; depth generation principle; duty-cycle control; frequency control; gesture control; gesture detection; gesture recognition; gesture tracking; human-computer interaction; image processing; light pulse adjustment; machine vision; near infrared illumination; overlapping feature processing; reconfigurable hardware architecture; reliability; single sensor NIR depth camera; smart TV; video game console control; Cameras; Games; Real-time systems; TV; Three-dimensional displays; Thumb; digital television systems; gesture control; human computer interfaces; real-time 3D camera technology; video game consoles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2014 IEEE International
  • Conference_Location
    Montevideo
  • Type

    conf

  • DOI
    10.1109/I2MTC.2014.6861016
  • Filename
    6861016