Literature DB >> 12938763

Image/source statistics of surfaces in natural scenes.

Zhiyong Yang1, Dale Purves.   

Abstract

Perceiving surfaces in a manner that accords with their physical properties is essential for successful behaviour. Since, however, a given retinal image can have been generated by an infinite variety of natural surfaces with different geometrical and/or physical qualities, the corresponding percepts cannot be determined by the stimulus per se. Rather, resolution of this quandary requires a strategy of vision that incorporates the statistical relationship of the information in retinal images to its sources in representative environments. To examine this probabilistic relationship with respect to the features of object surfaces, we analysed a database of range images in which the distances of all the objects in a series of natural scenes were measured with respect to the image plane by a laser range scanner. By taking any particular scene obtained in this way to be made up of a set of concatenated surface patches, we were able to explore the statistics of scene roughness, size-distance relationships, surface orientation and local curvature, as well as the independent components of natural surfaces. The relevance of these statistics to both perception and the neuronal organization of the underlying visual circuitry is discussed.

Mesh:

Year:  2003        PMID: 12938763

Source DB:  PubMed          Journal:  Network        ISSN: 0954-898X            Impact factor:   1.273


  14 in total

1.  The statistical structure of natural light patterns determines perceived light intensity.

Authors:  Zhiyong Yang; Dale Purves
Journal:  Proc Natl Acad Sci U S A       Date:  2004-05-19       Impact factor: 11.205

2.  Natural-scene statistics predict how the figure-ground cue of convexity affects human depth perception.

Authors:  Johannes Burge; Charless C Fowlkes; Martin S Banks
Journal:  J Neurosci       Date:  2010-05-26       Impact factor: 6.167

3.  The Poggendorff illusion explained by natural scene geometry.

Authors:  Catherine Q Howe; Zhiyong Yang; Dale Purves
Journal:  Proc Natl Acad Sci U S A       Date:  2005-05-11       Impact factor: 11.205

4.  Perceptual learning depends on perceptual constancy.

Authors:  Patrick Garrigan; Philip J Kellman
Journal:  Proc Natl Acad Sci U S A       Date:  2008-02-04       Impact factor: 11.205

5.  Depth variation and stereo processing tasks in natural scenes.

Authors:  Arvind V Iyer; Johannes Burge
Journal:  J Vis       Date:  2018-06-01       Impact factor: 2.240

6.  Estimating 3D tilt from local image cues in natural scenes.

Authors:  Johannes Burge; Brian C McCann; Wilson S Geisler
Journal:  J Vis       Date:  2016-10-01       Impact factor: 2.240

7.  The Southampton-York Natural Scenes (SYNS) dataset: Statistics of surface attitude.

Authors:  Wendy J Adams; James H Elder; Erich W Graf; Julian Leyland; Arthur J Lugtigheid; Alexander Muryy
Journal:  Sci Rep       Date:  2016-10-26       Impact factor: 4.379

8.  The effect of image position on the Independent Components of natural binocular images.

Authors:  David W Hunter; Paul B Hibbard
Journal:  Sci Rep       Date:  2018-01-11       Impact factor: 4.379

9.  Accuracy Maximization Analysis for Sensory-Perceptual Tasks: Computational Improvements, Filter Robustness, and Coding Advantages for Scaled Additive Noise.

Authors:  Johannes Burge; Priyank Jaini
Journal:  PLoS Comput Biol       Date:  2017-02-08       Impact factor: 4.475

10.  Multi-scale spatial concatenations of local features in natural scenes and scene classification.

Authors:  Xiaoyuan Zhu; Zhiyong Yang
Journal:  PLoS One       Date:  2013-09-30       Impact factor: 3.240

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