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Wendy Adams, Erich W. Graf, James H. Elder; Natural scene statistics and estimation of shape and reflectance.. Journal of Vision 2016;16(12):6. doi: 10.1167/16.12.6.
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© ARVO (1962-2015); The Authors (2016-present)
A major function of the visual system is to estimate the shape and reflectance of objects and surfaces from the image. Evidence from both human and computer vision suggests that solutions to this problem involve exploiting prior probability distributions over shape, reflectance and illumination. In an optimal system, these priors would reflect the statistics of our world. To allow a better understanding of the statistics of our environment, and how these statistics shape human perception, we have developed the Southampton-York Natural Scenes (SYNS) public dataset. The dataset includes scene samples from a wide variety of indoor and outdoor scene categories. Each scene sample consists of (i) 3D laser range (LiDAR) data over a nearly spherical field of view, co-registered with (ii) spherical high dynamic range imagery, and (iii) a panorama of stereo image pairs. These data are publicly available at https://syns.soton.ac.uk/. I will discuss a number of challenges that we have addressed in the course of this project, including: 1) geographic sampling strategy, 2) scale selection for surface analysis, 3) relating scene measurements to human perception. I will also discuss future work and potential applications.
Meeting abstract presented at VSS 2016
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