Computational Modeling of Vision: The Role of Combination
Defines a unified theory of vision in which nearly independent components of visual stimuli are recombined and synthesized at high levels of neural processing to produce the richness of visual experience. The text illustrates how visual systems gather, process and reconstruct information about objects in two and three dimensions.
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algorithm anatomical approach attributes basis functions behavior Bezier brain categorization channels chapter chromatic Clough-Tocher color combination components computational model computer vision cones cues data elements data fusion data sites defined Dempster-Shafer theory depth values described DeValois developed discussion disparity domain encoded estimates example Figure fuzzy logic global intensity interactions interpolant lateral geniculate lateral geniculate nucleus linear logic mathematical method minimization modules motion nervous system neural neurons object observer opsin Optical organic output particle pathway pattern perception perceptual experience physiological pixels possible premise present probability measure problem procedure produce psychophysical quadratic functionals receptor reconstruction regions representation represented retina scene segmentation sensitivity SFS algorithm SFSL shape contours shown in Fig simulated solution spatial specific stereo stimulus stripes subcomponent superior colliculus surface shape SWIMMER technique texture theory three-dimensional tion triangular patch triangulation trichromatic two-dimensional Uttal vertices vision system visual perception visual system wavelength