Bayesian paradigm for recognition of objects — Innovative applications

  • J. K. Aggarwal
  • Shishir Shah
Session S1A: Recent Advances in Computer Vision

DOI: 10.1007/3-540-63931-4_227

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1352)
Cite this paper as:
Aggarwal J.K., Shah S. (1997) Bayesian paradigm for recognition of objects — Innovative applications. In: Chin R., Pong TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1352. Springer, Berlin, Heidelberg

Abstract

This paper describes three innovative uses of the Bayesian paradigm for recognition of objects. A brief overview of the recognition problem and the use of the statistical approach are provided, along with the various stages for solving a problem. In addition, the paper presents formulations and results obtained by using Bayesian approaches in recent applications: human motion tracking, texture segmentation, and target recognition.

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Copyright information

© Springer-Verlag 1997

Authors and Affiliations

  • J. K. Aggarwal
    • 1
  • Shishir Shah
    • 1
  1. 1.Computer and Vision Research Center Department of Electrical and Computer EngineeringThe University of Texas at AustinAustinUSA

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