Title :
Depth Perception Model Based on Fixational Eye Movements Using Bayesian Statistical Inference
Author_Institution :
Fac. of Syst. Design, Tokyo Metropolitan Univ., Tokyo, Japan
Abstract :
Small vibrations of eyeball, which occur when we fix our gaze on object, is called "fixational eye movements.\´\´ It has been reported that such the involuntary eye movements work also for monocular depth perception. In this study, we focus on "tremor\´\´ which is the smallest type of fixational eye movement, and construct depth perception model based on tremor using MAP-EM algorithm. Its effectiveness is confirmed through numerical evaluations using artificial images.
Keywords :
Bayes methods; expectation-maximisation algorithm; image processing; visual perception; Bayesian statistical inference; MAP-EM algorithm; artificial images; depth perception model; eyeball small vibrations; fixational eye movements; involuntary eye movements; monocular depth perception; numerical evaluations; tremor; Adaptive optics; Computational modeling; Equations; Integrated optics; Mathematical model; Optical imaging; Pixel; Bayesian estimation; depth perception; fixational eye movement; structure from motion;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.411
