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Perceptual Organization of Shape

  • Chapter
Shape Perception in Human and Computer Vision

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

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.

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Acknowledgements

The author would like to thank Francisco Estrada, Tim Oleskiw, Gabriel Peyré, Ljiljana Velisavljević and Alexander Yakubovich for their contributions to the work reviewed in this chapter. This work was supported by NSERC, OCE and GEOIDE.

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Authors and Affiliations

  1. Centre for Vision Research, York University, Toronto, Canada

    James H. Elder

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  1. James H. Elder
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Correspondence to James H. Elder .

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Editors and Affiliations

  1. Department of Computer Science, University of Toronto, King's College Road 6, Toronto, M5S 3G4, Ontario, Canada

    Sven J. Dickinson

  2. Department of Psychological Sciences, Purdue University, Third Street 703, West Lafayette, 47907, Indiana, USA

    Zygmunt Pizlo

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Elder, J.H. (2013). Perceptual Organization of Shape. In: Dickinson, S., Pizlo, Z. (eds) Shape Perception in Human and Computer Vision. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-5195-1_5

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  • DOI: https://doi.org/10.1007/978-1-4471-5195-1_5

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5194-4

  • Online ISBN: 978-1-4471-5195-1

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