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The Statistics of Shape, Reflectance, and Lighting in Real-World Scenes

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Shape Perception in Human and Computer Vision

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

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Abstract

2D images are highly ambiguous representations of 3D scenes, and this poses a fundamental obstacle to recovering shape and reflectance from shaded images. A Bayesian approach to overcoming this problem is to exploit statistical regularities in surface shapes, reflectances, and lighting conditions in real world scenes, in order to choose the most likely 3D interpretation of a 2D image. Here I review recent work on the statistical regularities in real world 3D scenes that biological or artificial visual systems could use to overcome image ambiguity, and psychophysical work on the assumptions that the human visual system relies on in order to perceive 3D scenes from 2D images.

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Notes

  1. 1.

    Belhumeur et al. showed that image ambiguity is limited to the GBR ambiguity for an observer who has images of an object under all possible distant point lighting conditions. This is important for understanding the limits of methods such as photometric stereo, but the ambiguity is much greater when the observer sees an object under just one lighting condition. This has sometimes not been understood, e.g., Todd [36] suggests that work on the GBR ambiguity shows that the ambiguity of 2D images is highly constrained.

  2. 2.

    Brewster [12] is often credited with discovering the light-from-above prior. In fact, he mostly elaborated Rittenhouse’s [33] observation that we perceive ambiguous shaded patterns as having a 3D shape that is consistent with whatever we believe about the lighting direction in the scene being viewed. Neither Rittenhouse nor Brewster suggested that we have a default assumption that light comes from overhead.

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Authors and Affiliations

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

    Richard F. Murray

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  1. Richard F. Murray
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Correspondence to Richard F. Murray .

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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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Murray, R.F. (2013). The Statistics of Shape, Reflectance, and Lighting in Real-World Scenes. 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_16

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  • DOI: https://doi.org/10.1007/978-1-4471-5195-1_16

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5194-4

  • Online ISBN: 978-1-4471-5195-1

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