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Fall 2015 Schedule
Winter 2016 Schedule

2013/10/11, ENGMC 103 (SoCS seminar room), 10:30 - 11:30

Perceptual Organization of Shape
James Elder , Center for Vision Research, York University

Area: vision


Humans are very good at rapidly detecting salient objects such as animals in complex natural scenes, and recent psychophysical results suggest that the fastest mechanisms underlying animal detection use contour shape as a principal discriminative cue. How does our visual system extract these contours so rapidly and reliably? While the prevailing computational model represents contours as Markov chains that use only first-order local cues to grouping, computer vision algorithms based on this model fall well below human levels of performance. Here we explore the possibility that the human visual system exploits higher-order shape regularities in order to segment object contours from cluttered scenes. In particular, we consider a recurrent architecture in which higher areas of the object pathway generate shape hypotheses that condition grouping processes in early visual areas. Such a generative model could help to guide local bottom-up grouping mechanisms toward globally consistent solutions. In constructing an appropriate theoretical framework for recurrent shape processing, a central issue is to ensure that shape topology remains invariant under all actions of the feedforward and feedback processes. This can be achieved by a promising new theory of shape representation based upon a family of local image deformations called formlets, shown to outperform alternative contour-based generative shape models on the important problem of visual shape completion.

Biography of Speaker:

James Elder received his PhD in Electrical Engineering from McGill University in 1996. He is currently a member of the Centre for Vision Research and a Professor in the Departments of Electrical Engineering and Computer Science and Psychology at York University. Dr. Elder’s research has won a number of awards and honours, including the Premier’s Research Excellence Award and the Young Investigator Award from the Canadian Image Processing and Pattern Recognition Society. His 3DTown research has recently been featured in the National Post and on CBC radio and television.