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Visual Perception by Computer
A Computer Vision Model
The Organization of this Thesis
29 other sections not shown
a a a adjustment routine approach array Binocular Cues boundaries camera cells chapter color combined computer vision model computer vision system context depth cues depth estimate depth perception described edge detection environment environmental model example G G G gions ground plane hypothesis H H H H heuristics house scene human vision imply input intensity labeled layer Leonard Uhr linear perspective long-term object models low level processing matching mental model object names occlusion Ohlander Ohlander's operator order statistics outdoor scenes output pattern recognition perceived perceptual psychology placement routine points problem recognition cone region descriptions region growing represented ri H ri ri Riseman saturation scene analysis segmentation algorithm semantic shape similar SIMULA specific stereopsis surface textural measures texture gradients thesis tion transforms tree visual knowledge routines visual perception visual system wall Yakimovsky's Zobrist Zobrist-Thompson