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A computational model for motion detection and direction discrimination in humans

Song, Yang and Perona, Pietro (2000) A computational model for motion detection and direction discrimination in humans. In: Workshop on Human Motion Proceedings. IEEE Computer Society , Los Alamitos, CA, pp. 11-16. ISBN 0-7695-0940-1.

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Seeing biological motion is very important for both humans and computers. Psychophysics experiments show that the ability of our visual system for biological motion detection and direction discrimination is different from that for simple translation. The existing quantitative models of motion perception cannot explain these findings. We propose a computational model, which uses learning and statistical inference based on the joint probability density function (PDF) of the position and motion of the body, on stimuli similar to (Neri et al., 1998). Our results are consistent with the psychophysics indicating that our model is consistent with human motion perception, accounting for both biological motion and pure translation.

Item Type:Book Section
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URLURL TypeDescription DOIArticle
Perona, Pietro0000-0002-7583-5809
Additional Information:© 2000 IEEE. Date of Current Version: 06 August 2002. Funded by the NSF Engineering Research Center for Neuromorphic Systems Engineering (CNSE) at Caltech (NSF9402726), and by an NSF National Young Investigator Award to PP (NSF9457618). We thank Peter Neri for providing the code of generating the human walking sequences [2].
Funding AgencyGrant Number
Center for Neuromorphic Systems Engineering, CaltechUNSPECIFIED
Record Number:CaltechAUTHORS:20111130-152242489
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Official Citation:Yang Song; Perona, P.; , "A computational model for motion detection and direction discrimination in humans," Human Motion, 2000. Proceedings. Workshop on , vol., no., pp.11-16, 2000 doi: 10.1109/HUMO.2000.897364 URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:28260
Deposited By: Tony Diaz
Deposited On:19 Jan 2012 19:07
Last Modified:26 Nov 2019 00:21

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