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.
This research was supported by ARO DAAH-94-G-0417 and DAAH 049510494.
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© 1997 Springer-Verlag Berlin Heidelberg
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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. https://doi.org/10.1007/3-540-63931-4_227
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DOI: https://doi.org/10.1007/3-540-63931-4_227
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