Motion segmentation in RGB image sequence based on hidden MRF and 6D Gaussian distribution

Adam Kurianski; Takeshi Agui; Hiroshi Nagahashi

doi:10.1117/12.233281

27 February 1996 Motion segmentation in RGB image sequence based on hidden MRF and 6D Gaussian distribution

Adam Kurianski, Takeshi Agui, Hiroshi Nagahashi

Proceedings Volume 2727, Visual Communications and Image Processing '96; (1996) https://doi.org/10.1117/12.233281
Event: Visual Communications and Image Processing '96, 1996, Orlando, FL, United States

Abstract

A problem of motion segmentation in RGB image sequence is addressed. An algorithm proposed is based on local motion modeling and pixel labeling approach. An information vector used for labeling consists of six components; three color components and three differences of colors. To develop the labeling algorithm a statistical model of motion sequence, which uses a six-variate Gaussian distribution, is chosen. Moreover, the use of a hidden Markov random field (MRF) framework is proposed in order to carry out the segmentation more accurately. The experimental results of the application of the method to an RGB sequence showing a woman's turning head are included and discussed.

Citation Download Citation

Adam Kurianski, Takeshi Agui, and Hiroshi Nagahashi "Motion segmentation in RGB image sequence based on hidden MRF and 6D Gaussian distribution", Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); https://doi.org/10.1117/12.233281

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