Abstract
We address the problem of contour inference from partial data, as obtained from state-of-the-art edge detectors.
We argue that in order to obtain more pereeptually salient contours, it is necessary to impose generic constraints such as continuity and co-curvilinearity.
The implementation is in the form of a convolution with a mask which encodes both the orientation and the strength of the possible continuations. We first show how the mask, called the “Extension field” is derived, then how the contributions from different sites are collected to produce a saliency map.
We show that the scheme can handle a variety of input data, from dot patterns to oriented edgels in a unified manner, and demonstrate results on a variety of input stimuli.
We also present a similar approach to the problem of inferring contours formed by end points. In both cases, the scheme is non-linear, non iterative, and unified in the sense that all types of input tokens are handled in the same manner.
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References
Ahuja, N. and Tuceryan, M. 1989. Extraction of early perceptual structure in dot patterns: Integrating region, boundary, and component Gestalt. CVGIP, 48:304–356.
Baliard, D.H. 1981. Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition, 13(2):111–122.
Boff, K.R., Kaufman, L., and Thomas, J.P. Handbook of Perception and Human Performance, John Wiley and Sons, Vol. II, pp. 36-1–36-30.
Clowes, M.B. 1971. On seeing things. Artificial Intelligence. 2(1):76–116.
Dolan, J. and Weiss, R. Perceptual grouping of curved lines. Proc. IUW89, Palo Alto, CA., pp. 1135–1145.
Duda, R.O and Hart, P.E. 1972. Use of the Hough transformation to detect lines and curves in pictures. Communications of the ACM, 15:11–15.
Guy, G. and Medioni, G. 1992. Perceptual grouping using global saliency enhancing operators. Proc. of ICPR92, The Hague, Holland, pp. 99–104.
Guy, G. and Medioni, G. 1995. Perceptual grouping using global saliency enhancing operators. IRIS-USC Technical report.
Heitger, F. and von der Heydt, R. 1993. A computational model of neural contour processing: Figure-ground segregation and illusory contours, Proc. of the ICCV, pp. 32–40.
Helson, H. 1933. The fundamental propositions of gestalt psychology. Psychological Review, 40:13–32.
Hough, P.V.C. 1962. A method and means for recognizing complex patterns. U.S. Patent No. 3,069,654.
Kanizsa, G.K. 1976. Subjective contours, Scientific American.
Koenderink, J.J. 1990. Solid Shape, The MIT Press, Cambridge.
Lowe, D.G. 1987. Three-dimensional object recognition from single two-dimensional images. Artificial Intelligence, 31:355–395.
Mohan. R. and Nevatia, R. 1989. Segmentation and description based on perceptual organization. Proc. CVPR, San Diego, Ca., pp. 333–341.
Mohan, R. and Nevatia, R. 1989. Using perceptual organization to extract 3-D structures. IEEE Trans. on PAMI, 11(11):1121–1139.
Parent, P. and Zucker, S.W., 1989. Trace inference, curvature consistency, and curve detection, IEEE Trans. PAMI, 11(8):823–839.
Parvin, B. and Medioni, G. 1991. A dynamic system for object description and correspondence. Proc. CVPR, Maui, Hawaii, pp. 393–399.
Perona, P. 1992. Steerable-scalable kernels for edge detection and junction analysis. Proc. ECCV, Santa Margherita Ligure, Italy, pp. 3–18.
Rock, I. and Palmer, S. 1990. The legacy of gestalt psychology, Scientific American, pp. 84–90.
Rom, H. and Medioni, G. 1993. Hierarchical decomposition and axial shape description. IEEE Trans. on PAMI, 15:973–981.
Sha'ashua, A. and Ullman, S. 1988. Structural saliency: The detection of globally salient structures using a locally connected network. Proc. ICCV, Tampa, FL., pp. 321–327.
Stein, F. and Medioni, G. 1992. Recognizing 3D Objects from 2D Groupings, IUW92, San Diego, Ca., pp. 667–674.
Sugihara, K. 1984. An algebraic approach to shape-from-image problems. Artificial Intelligence, 23(1):59–95.
Ullman, S. 1976. Filling-in the gaps: The shape of subjective contours and a model for their generation. Biological Cybernetics, 25:1–6.
Ulupinar, F. 1993. Perception of 3-D surfaces from 2-D contours. IEEE Trans. on PAMI, 15:592–597.
Waltz, D.I. Generating semantic descriptions from drawings of scenes with shadows. P.H. Winston (Ed.), Chapter 3 in The Psychology of Computer Vision, McGraw Hill, New York.
Wertheimer, M. 1929. Untersuchungen zur Lehre von der Gestalt. II. Psychologische Forrschung, (English translation), 4:301–350.
Williams, L.R. and Jacobs, D.W. 1995. Stochastic completion fields: A neural model of illusory contour shape and salience. Proc. of the 5th Int'l Conf. on Computer Vision, Cambridge, Mass.
Zucker, S.W., Dobbins, A., David, C., and Iverson, L. 1988. The organization of curve detection: Coarse tangent fields and fine spline coverings. Proc. ICCV, Tampa, FL., pp. 568–577.
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This research was supported by the Advanced Research Projects Agency of the Department of Defense and was monitored by the Air Force Office of Scientific Research under Contract No. F49620-90-C-0078, and by a NSF Grant under award No. IRI-9024369. The United States Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation hereon.
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Guy, G., Medioni, G. Inferring global pereeptual contours from local features. Int J Comput Vision 20, 113–133 (1996). https://doi.org/10.1007/BF00144119
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DOI: https://doi.org/10.1007/BF00144119