Video arrays for real-time tracking of person, head, and face in an intelligent room

  • Authors:
  • Kohsia S. Huang;Mohan M. Trivedi

  • Affiliations:
  • Computer Vision and Robotics Research (CVRR) Laboratory, University of California San Diego, 9500 Gilman Drive, La Jolla, CA;Computer Vision and Robotics Research (CVRR) Laboratory, University of California San Diego, 9500 Gilman Drive, La Jolla, CA

  • Venue:
  • Machine Vision and Applications - Special issue: Omnidirectional vision and its applications
  • Year:
  • 2003

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Abstract

Real-time three-dimensional tracking of people is an important requirement for a growing number of applications. In this paper we describe two trackers; both of them use a network of video cameras for person tracking. These trackers are called a rectilinear video array tracker (R-VAT) and an omnidirectional video array tracker (O-VAT), indicating the two different ways of video capture. The specific objectives of this paper are twofold: (i) to present a systematic comparison of these two trackers using an extensive series of experiments conducted in an 'intelligent' room; (ii) to develop a real-time system for tracking the head and face of a person, as an extension of the O-VAT approach. The comparative research indicates that O-VAT is more robust to the number of people, less complex and runs faster, needs manual camera calibration, and the integrated omnidirectional video network has better reconfigurability. The person head and face tracker study shows that such a system can serve as a most effective input stage for face recognition and facial expression analysis modules.