Abstract
A common factor in all illusory contour figures is the perception of a surface occluding part of a background. These surfaces are not constrained to be at constant depth and they can cross other surfaces. We address the problem of how the image organizations that yield illusory contours arise. Our approach is to iteratively find the most salient surface by (i) detecting occlusions; (ii) assigning salient-surface-states, a set of hypothesis of the local salient surface configuration; (iii, applying a Bayesian model to diffuse these salient-surface-states; and (iv) efficiently selecting the best image organization (set of hypothesis) based on the resulting diffused surface.
We note that the illusory contours arise from the surface boundaries and the amodal completions emerge at the overlapping surfaces. The model reproduces various qualitative and quantitative aspects of illusory contour perception.
Chapter PDF
References
E. Adelson and P. Anandan. Ordinal characteristics of transparency. In Proc. AAAI Workshop on Qualitative Vision, pages 552–573, Los Angeles, CA, 1990.
D. J. Amit, H. Gutfreund, and H. Sompolinsky. Spin-glass models of neural networks. Physical Review A, 32:1007–1018, 1985.
M. Brady and W. E. L. Grimson. The perception of subjective surfaces. A.I. Memo No. 666, AI Lab., MIT, Nov. 1982.
T. Darrell and A. Pentland. Cooperative robust estimation using layers of support. IEEE Trans. PAMI, PAMI-17(5):474–487, 1995.
R. von der Heydt. E. Peterhans and G. Baumgartner. Neuronal responses to illusory contour stimuli reveal stages of visual cortical processing. In Visual Neuroscience, pages 343–351. Cambridge U.P, 1986.
D. Geiger and F. Girosi. Parallel and deterministic algorithms for mrfs: surface reconstruction. IEEE Trans. PAMI, PAMI-13(5):401–412, May 1991.
D. Geiger, B. Ladendorf, and A. Yuille. Binocular stereo with occlusion. In 2nd ECCV, Santa Marguerita, Italy, May 1992. Springer-Verlag.
D. Geiger and A. Yuille. A common framework for image segmentation. International Journal of Computer Vision, 6:3:227–243, August 1991.
G.Guy and G. Medioni. Inferring global perceptual contours from local features. In Proc. Image Understanding Workshop DARPA, September 1992.
S. Grossberg and E. Mingolla. Neural dynamics of perceptual grouping:textures, boundaries and emergent segmentations. Perception & Psychophysics, 38(2):141–170, 1985.
Stephen Grossberg. 3-d vision and figure-ground separation by visual cortex. Perception & Psychophysics, 55(1):48–120, 1994.
F. Heitger and R. von der Heydt. A computational model of neural contour processing: Figure-ground segregation and illusory contours. Proceedings of the IEEE, pages 32–40, 1993.
S. Hsu, P. Anandan, and S. Peleg. Accurate computation of optical flow by using layered motion representation. In ICPR, pages 743–746, Oct 1994.
D.A. Huffman. A duality concept for the analysis of polyhedral scenes. In Machine Intelligence, volume 6. Edinb. Univ. Press, Edinb., U.K., 1971.
Bela Julesz. Textons: the elements of texture perception, and their interactions. Nature, 290:91–97, March 1981.
A. Kamath and N. Karmarkar. A continuous approach to compute upper bounds in quadratic minimization problems with integer constraints. In C. A. Floudas and P. M. Pardalos, ed., Recent Adv. in Global Opt., volume 2, 229–241, 1991.
G. Kanizsa. Organization in Vision. Praeger, New York, 1979.
P.J. Kellman and T.F. Shipley. A theory of visual interpolation in object perception. Cognitive Psychology, 23:141–221, 1995.
K. Kumaran, D. Geiger, and L. Gurvits. Illusory surfaces and visual organization. Network:Computation in Neural Systems, 7(1), February 1996.
D. Mumford. Elastica and computer vision. In C. L. Bajaj, editor, Algebraic Geometry and Its Applications. Springer-Verlag, New York, 1993.
Nitzberg, Mumford, and Shiota. Filtering, Segmentation, and Depth. Springer-Verlag, New York, 1993.
M. Nitzberg and D. Mumford. The 2.1-d sketch. In Proceedings of the International Conference on Computer Vision, pages 138–144. IEEE, DC, 1990.
D. L. Ringach and R. Shapley. The dynamics of illusory contour integration. Investigative Ophthalmology and Visual Science, 35,#2:4196-, 1994.
D. L. Ringach and R. Shapley. Similar mechanisms for illusory contour and amodal completion. Investigative Ophthalmology and Visual Science, 35,#2:1089-, 1994.
A. Shashua and S. Ullman. Structural saliency: The detection of globally salient structures using a locally connected network. In Proceedings of the International Conference on Computer Vision, pages 321–327, 1988.
F. Shumann. Einige beobachtungen uber die zusammenfassung von gesichtseindrucken zu einheiten. Physiologische Studien, 1:1–32, 1904.
S. Ullman. Filling in the gaps: The shape of subjective contours and a model for their generation. Biological Cybernetics, 25:1–6, 1976.
R. von der Heydt, E. Peterhans, and G. Baumgartner. Illusory contours and cortical neuron responses. Science Washington, 224:1260–1262, 1984.
L. R. Williams and A.R. Hanson. Perceptual completion of occluded surfaces. Proc. of IEEE Computer Vision and Pattern Recognition, 1994.
L. R. Williams and D.W. Jacobs. Stochastic completion fields: A neural model of illusory contour shape and salience. Proc. of 5th Intl. Conf. on Comp. Vision, 1995.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1996 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Geiger, D., Kumaran, K. (1996). Visual organization of illusory surfaces. In: Buxton, B., Cipolla, R. (eds) Computer Vision — ECCV '96. ECCV 1996. Lecture Notes in Computer Science, vol 1064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0015554
Download citation
DOI: https://doi.org/10.1007/BFb0015554
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-61122-6
Online ISBN: 978-3-540-49949-7
eBook Packages: Springer Book Archive