140
Views
22
CrossRef citations to date
0
Altmetric
Original Article

Image/source statistics of surfaces in natural scenes

&
Pages 371-390 | Received 13 Sep 2002, Published online: 09 Jul 2009

References

  • Hershenson M. Visual Space Perception: A Primer. MIT Press, Cambridge, MA 1999
  • Palmer S. Vision Science. MIT Press, Cambridge, MA 2000
  • Gillam B. The perception of spatial layout from static optical information. Perception of Space and Motion, W Epstein, S Rogers. Academic, New York 1995; 23–67
  • Coren S, Girgus J S. Seeing is Deceiving: The Psychology of Visual Illusions. Erlbaum, Hillsdale 1978
  • Robinson J O. The Psychology of Visual Illusion. Dover, New York 1998
  • Knill D C, Richards W. Perception as Bayesian Inference, D C Knill, W Richards. Cambridge University Press, Cambridge 1996
  • Rao R P N, Olshausen B A, Lewicki M S. Probabilistic Models of the Brain, R P N Rao, B A Olshausen, M S Lewicki. MIT Press, Cambridge, MA 2002
  • Purves D, Lotto B. Why We See What We Do: An Empirical Theory of Vision. Sinauer Associates, Sunderland, MA 2002
  • Howe C Q, Purves D. The statistics of range images can explain the anomalous perception of length. Proc. Natl Acad. Sci. USA 2003; 99: 13184–8
  • Huang J, Lee A B, Mumford D. Statistics of range images. Proc. IEEE Conf. CVPR 2000; 1: 324–31
  • Simoncelli E P, Olshausen B A. Natural image statistics and neural representation. Annu. Rev. Neurosci. 2001; 24: 1193–216
  • Ruderman D L. Origins of scaling in natural images. Vis. Res. 1997; 37: 3385–98
  • Mumford D, Gidas B. Stochastic models for generic images. Q. Appl. Math. 2001; 59: 85–111
  • Lee A B, Mumford D, Huang J. Occlusion models for natural images: a statistical study of a scale-invariant dead leaves model. Int. J. Comput. Vis. 2001; 41: 35–59
  • Hyvärinen A, Oja E. A fast fixed-point algorithm for independent component analysis. Neural Comput. 1997; 9: 1483–92
  • Ruderman D L, Bialek W. Statistics of natural images: scaling in the woods. Phys. Rev. Lett. 1994; 73: 814–17
  • Olshausen B A, Field D J. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature 1996; 381: 607–9
  • Van Hateren J H, Van der Schaaf A. Independent component filters of natural images compared with simple cells in primary visual cortex. Proc. R. Soc. 1998; 265: 359–66
  • Van Hateren J H, Ruderman D L. Independent component analysis of natural image sequences yields spatiotemporal filters similar to simple cells in primary visual cortex. Proc. R. Soc. 1998; 265: 2315–20
  • Olshausen B A, Field D J. Sparse coding with an overcomplete basis set: A strategy employed by V1?. Vis. Res. 1997; 37: 3311–25
  • Marr D. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. Freeman, San Francisco, CA 1982
  • Sajda P, Finkel L H. Intermediate-level visual representations and the construction of surface perception. J. Cog. Neurosci. 1995; 7: 267–91
  • Adelson E H. Lightness perception and lightness illusions. The New Cognitive Neuroscience, M S Gazzaniga. MIT Press, Cambridge, MA 2000; 339–51
  • Bulthoff H, Mallot H A. Interaction of different modules in depth perception. J. Opt. Soc. Am. 1988; 5: 1749–58
  • Koenderink J J, Van Doorn A J, Kappers A M L. Pictorial surface attitude and local depth comparisons. Percept Psychophys. 1996; 58: 163–73
  • Yang Z, Purves D. A statistical explanation of visual space. Nature, Neurosci. 2003, at press
  • Barlow H B. Unsupervised learning. Neural Comput. 1989; 1: 295–311
  • Laughlin S B. Matching coding, circuits, cells, and molecules to signals. General principles of retinal design in the fly's eye. Prog. Retinal Eye Res. 1994; 13: 165–96
  • Atick J J. Could information theory provide an ecological theory of sensory processing?. Network: Comput. Neural Syst. 1992; 3: 213–51
  • Field D. What is the goal of sensory coding?. Neural Comput. 1994; 6: 559–601
  • Ruderman D L, Cronin T W, Chiao C C. Statistics of cone responses to natural images: implications for visual coding. J. Opt. Soc. Am. A 1998; 15: 2036–45
  • Theunissen F E, et al. Estimating spatio-temporal receptive fields of auditory and visual neurons from their responses to natural stimuli. Network: Comput. Neural Syst. 2001; 12: 289–316
  • Lewen G D, Bialek W, de Ruyter van Steveninck R. Neural coding of naturalistic motion stimuli. Network: Comput. Neural Syst. 2001; 12: 317–29
  • Hyvärinen A, Hoyer P O. A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images. Vis. Res. 2001; 41: 2413–23
  • Geisler W S, Perry J S, Super B J, Gallogly D P. Edge co-occurrence in natural images predicts contour grouping performance. Vis. Res. 2001; 41: 711–24
  • Edler J H, Goldberg R M. Ecological statistics of Gestalt laws for the perceptual organization of contours. J. Vis. 2002; 2: 324–53, http://journalofvision.org/2/4/5/, DOI 10.1167/2.4.5
  • Barlow H B. Redundancy reduction revisited. Network: Comput. Neural Syst. 2001; 12: 241–53
  • Kersten D. High-level vision as statistical inference. The New Cognitive Neuroscience, M S Gazzaniga. MIT Press, Cambridge, MA 2000; 353–63

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.