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DOI: 10.14569/IJACSA.2013.040511
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A Computational Model of Extrastriate Visual Area MT on Motion Perception

Author 1: Jiawei Xu
Author 2: Shigang Yue

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 5, 2013.

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Abstract: Human vision system are sensitive to motion perception under complex scenes. Building motion attention models similar to human visual attention system should be very beneficial to computer vision and machine intelligence; meanwhile, it has been a challenging task due to the complexity of human brain and limited understanding of the mechanisms underlying the human vision system. This paper models the motion perception mechanisms in human extrastriate visual middle temporal area (MT) computationally. MT is middle temporal area which is sensitive on motion perception. This model can explain the attention selection mechanism and visual motion perception to some extent. With the proposed model, we analysis the motion perception under day time with single or multiple moving objects, we then mimic the visual attention process consisting of attention shifts and eye fixations against motion- feature-map. The model produced similar gist perception outputs in our experiments, when day-time images and nocturnal images from the same scene are processed. At last, we mentioned the future direction of this research.

Keywords: Motion perception; daytime and nocturnal scenes; spatio-temporal phase

Jiawei Xu and Shigang Yue. “A Computational Model of Extrastriate Visual Area MT on Motion Perception”. International Journal of Advanced Computer Science and Applications (IJACSA) 4.5 (2013). http://dx.doi.org/10.14569/IJACSA.2013.040511

@article{Xu2013,
title = {A Computational Model of Extrastriate Visual Area MT on Motion Perception},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2013.040511},
url = {http://dx.doi.org/10.14569/IJACSA.2013.040511},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {5},
author = {Jiawei Xu and Shigang Yue}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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