Bayesian estimation of smooth object motion using data from direction-sensitive velocity sensors

David Yushan Fong; Carlos A. Pomalaza-Raez

doi:10.1117/12.48375

1 October 1991 Bayesian estimation of smooth object motion using data from direction-sensitive velocity sensors

David Yushan Fong, Carlos A. Pomalaza-Raez

Proceedings Volume 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision; (1991) https://doi.org/10.1117/12.48375
Event: San Diego, '91, 1991, San Diego, CA, United States

Abstract

A two-stage process involving Bayesian estimates of smooth velocity vectors is used to detect physical object movements in an image sequence containing noisy background motions. This process computes the probability that a velocity vector is `smooth' with respect to a vector in the previous frame. Those vectors with a high probability are assembled into `paths' and paths longer than a threshold are retained. When this process is applied to the output of a velocity- sensitive network, random movements from the background are filtered out from the sequence, retaining only the smooth motion vectors.

Citation Download Citation

David Yushan Fong and Carlos A. Pomalaza-Raez "Bayesian estimation of smooth object motion using data from direction-sensitive velocity sensors", Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); https://doi.org/10.1117/12.48375

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