Session S1A: Recent Advances in Computer Vision

Computer Vision — ACCV'98

Volume 1352 of the series Lecture Notes in Computer Science pp 275-282

Date:

Bayesian paradigm for recognition of objects — Innovative applications

  • J. K. AggarwalAffiliated withComputer and Vision Research Center Department of Electrical and Computer Engineering, The University of Texas at Austin
  • , Shishir ShahAffiliated withComputer and Vision Research Center Department of Electrical and Computer Engineering, The University of Texas at Austin

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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.