Hybrid layered video encoding for mobile internet-based computer vision and multimedia applications

  • Authors:

  • Suchendra M. Bhandarkar;Siddhartha Chattopadhyay;Shiva Sandeep Garlapati

  • Affiliations:

  • Department of Computer Science, The University of Georgia, Athens, GA;Google Inc., Mountain View;Department of Computer Science, The University of Georgia, Athens, GA

  • Venue:
  • Mobile Multimedia Processing
  • Year:
  • 2010

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Abstract

Mobile networked environments are typically resource constrained in terms of the available bandwidth and battery capacity on mobile devices. Real-time video applications entail the analysis, storage, transmission, and rendering of video data, and are hence resource-intensive. Since the available bandwidth in the mobile Internet is constantly changing, and the battery life of a mobile video application decreases with time, it is desirable to have a video representation scheme that adapts dynamically to the available resources. A Hybrid Layered Video (HLV) encoding scheme is proposed, which comprises of content-aware, multi-layer encoding of texture and a generative sketch-based representation of the object outlines. Different combinations of the texture- and sketch-based representations result in distinct video states, each with a characteristic bandwidth and power consumption profile. The proposed HLV encoding scheme is shown to be effective for mobile Internet-based multimedia applications such as background subtraction, face detection, face tracking and face recognition on resource-constrained mobile devices.