Asynchronous Perceptual Grouping: From Contours to Relevant 2-D Structures

Computer Vision and Image Understanding

Volumn 66, Issue 1, 1997, Pages 1-24

  Jacot Descombes, Alain ^a,b   Pun, Thierry ^a  

^a UNIVERSITY OF GENEVA   (Switzerland)

^b ELECTROTECHNICAL LABORATORY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL GEOMETRY; FEATURE EXTRACTION; IMAGE PROCESSING; MATHEMATICAL MORPHOLOGY; OBJECT RECOGNITION;

ASYNCHRONOUS PERCEPTUAL GROUPING;

COMPUTER VISION;

EID: 0031117966     PISSN: 10773142     EISSN: None     Source Type: Journal    
DOI: 10.1006/cviu.1996.0509     Document Type: Article

References (48)

1. D. H. Ballard and C. M. Brown, Computer Vision, Prentice-Hall, Englewood Cliffs, NJ, 1982.
2. R. Bergevin and M. D. Levine, Generic object recognition: Building and matching coarse descriptions from line drawings, IEEE Trans. Pattern Anal. Mach. Intell. 15, 1993, 19-36.
3. I. Biederman, Human image understanding: Recent research and a theory, Comput. Vision Graphics Image Process. 32, 1985, 29-73.
4. I. Biederman, J. E. Hummel, P. C. Gerhardstein, and E. E. Cooper, From image edges to geons to viewpoint invariant object models: A neural net implementation, in Proceedings, Applications of Artificial Intel. X: Machine Vision and Robotics, Orlando, 1992, SPIE vol. 1708, pp. 570-578, SPIE - Int. Soc. Opt. Eng., Bellingham, WA.
5. J.-M. Bost, R. Milanese, and T. Pun, Temporal precedence is asynchronous visual indexing, in Lecture Notes in Computer Science, CAIP'93 (D. Chetverikov and W. G. Kropatsch, Eds.), vol. 719, pp. 468-475, Springer-Verlag, New York, 1993.
6. P.-Y. Burgi and T. Pun, Temporal analysis of contrast and geometric selectivity in early human visual system, in Channels in the Visual Nervous System: Neurophysiology, Psychophysics, Models (B. Blum, Ed.), Freund, London/Tel Aviv, 1991.
7. P.-Y. Burgi and T. Pun, Asynchronous image analysis: Using the relationship luminance-to-latency to improve segmentation, J. Opt. Soc. Am. 11, 1994, 1720-1726.
8. J. Canny, A computational approach to edge detection, IEEE Trans. Pattern Anal. Mach. Intell. 8, 1986, 679-698.
9. N. Christofides, Graph Theory: An Algorithmic Approach, Academic Press, London, UK, 1975.
10. D. T. Clemens, Region-based feature interpretation for recognizing 3-D models in 2-D images, MIT AI Lab Technical Report, 1307, June 1991.
11. S. J. Dickinson, A. P. Pentland, and A. Rosenfeld, From volumes to views: An approach to 3-D object recognition, CVGIP: Image Understanding 55, 1992, 130-154.
12. S. J. Dickinson, A. P. Pentland, and A. Rosenfeld, 3-D shape recovery using distributed aspect matching, IEEE Trans. Pattern Anal. Mach. Intell. 14, 1992, 174-198.
13. S. J. Dickinson, H. I. Christensen, J. Tsotsos, and G. Olofsson, Active object recognition integrating attention and viewpoint control, in Lecture Notes in Computer Science, Computer Vision - ECCV'94 (J.-O. Eklundh, Ed.), vol. 801, pp. 3-14, Springer-Verlag, New York, 1994.
14. R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis, Wiley, New York, 1973.
15. P. J. Flynn, Saliencies and symmetries: Toward 3D object recognition from large model databases, in Proceedings, CVPR '92, 1992, pp. 322-327.
16. W. E. L. Grimson, Object Recognition by Computer: The Role of Geometric Constraints, MIT Press, Cambridge, MA, 1990.
17. P. Havaldar, G. Medioni, and F. Stein, Extraction of groups for recognition, in Lecture Notes in Computer Science, Computer Vision - ECCV'94 (J.-O. Eklundh, Ed.), vol. 800, pp. 251-261, Springer-Verlag, New York, 1994.
18. F. Heitger, L. Rosethaler, R. von der Heydt, R. Peterhans, and O. Kubler, Simulation of neural contour mechanisms: From simple to end-stopped cells, Vision Res. 32, 1992, 963-981.
19. R. Horaud, F. Veillon, and T. Skordas, Finding geometric and relational structures in an image, in Proceedings, 1st European Conf. Comput. Vision - ECCV90, Antibes, France, 1990, pp. 374-384.
20. D. P. Huttenlocher and P. C. Wayner, Finding convex edge groupings in an image, Int. J. Comput. Vision 8, 1992, 7-27.
21. A. Jacot-Descombes and T. Pun, A probabilistic approach to 3-D inference of geons from a 2-D view, in Proceedings, Applications of Artificial Intell. X: Machine Vision and Robotics, Orlando, 1992, SPIE vol. 1708, pp. 579-588, SPIE - Int. Soc. Opt. Eng., Bellingham, WA.
22. A. Jacot-Descombes, Groupage perceptuel asynchrone pour la compréhension qualitative d'images: des contours aux primitives génériques, Ph.D. thesis in computer science, University of Geneva, Edition Systèmes et Information, Geneva, Switzerland, 1993.
23. T. Kitahashi, M. Ashida, S. Dan, and H. Ogawa, The 'Functant' in a functional model: A theoretical consideration of reasoning about shape, structure and function, in Proceedings, Applications of Artificial Intell. X: Machine Vision and Robotics, Orlando, 1992, SPIE vol. 1708, pp. 561-568, SPIE - Int. Soc. Opt. Eng., Bellingham, WA.
24. D. G. Lowe, Perceptual Organization and Visual Recognition, Kluwer Academic, Norwell, MA, 1985.
25. D. G. Lowe, Organization of smooth image curves at multiple scales, Int. J. Comput. Vision 3, 1989, 119-130.
26. H. Q. Lu and J. K. Aggarwal, Applying perceptual organization to the detection of manmade objects in non-urban scenes, Pattern Recognit. 25, 1992, 835-853.
27. J. Malik, Interpreting line drawings of curved objects. Int. J. Comput. Vision 1, 1987, 73-103.
28. J. D. McCafferty, Human and Machine Vision: Computing Perceptual Organisation, Ellis Horwood, Chichester, UK, 1990.
29. D. Metaxas and S. J. Dickinson, Integration of quantitative and qualitative techniques for deformable model fitting from orthographic, perspective and stereo projections, in Proceedings, ICCV'93, 1993, pp. 641-649.
30. M. Minoux and G. Bartnik, Graphes Algorithmes Logiciels, Dunod informatique, Bordas, Paris, 1986.
31. R. Mohan and R. Nevatia, Using perceptual organization to extract 3-D structures, IEEE Trans. Pattern Anal. Mach. Intell. 11, 1989, 1121-1139.
32. R. Mohan and R. Nevatia, Perceptual organization for scene segmentation and description, IEEE Trans. Pattern Anal. Mach. Intell. 14, 1992, 616-635.
33. F. Mokhtarian and A. K. Mackworth, Scale-based description and recognition of planar curves and two-dimensional shapes, IEEE Trans. Pattern Anal. Mach. Intell. 8, 1986, 34-43.
34. R. C. Munck-Fairwood, Recognition of geometric primitives using logic-program and probabilistic-network reasoning methods, in Proceedings, Applications of Artificial Intell. X: Machine Vision and Robotics, Orlando, 1992, SPIE vol. 1708, pp. 589-600, SPIE - Int. Soc. Opt. Eng., Bellingham, WA.
35. S. Negahdaripour and A. K. Jain, Challenges in computer vision: Future research directions, in Proceedings, CVPR '92, 1992, pp. 189-199.
36. T. Pun, J.-M. Bost, R. Milanese, C. Rauber, and S. Startchik, Selecting relevant information and delaying irrelevant data for objects recognition, in AAAI-94 Fall Symposium Series, "Relevance," New Orleans, 1994, (R. Greiner and D. Subramanian, Eds.), pp. 168-172.
37. N. S. Raja and A. K. Jain, Obtaining generic parts from range data using a multi-view representation, in Proceedings, Applications of Artificial Intell. X: Machine Vision and Robotics, Orlando, 1992, SPIE vol. 1708, pp. 602-613, SPIE - Int. Soc. Opt. Eng., Bellingham, WA.
38. N. S. Raja and A. K. Jain, Obtaining generic parts from range images using a multi-view representation, CVGIP: Image Understanding 60, 1994, 44-64.
39. S. Sarkar and K. L. Boyer, Perceptual organization in computer vision: A review and a proposal for a classificatory structure, IEEE Trans. Syst. Man Cybernet. 23, 1993, 382-399.
40. S. Sarkar and K. L. Boyer, A computational structure for preattentive perceptual organization: Graphical enumeration and voting methods, IEEE Trans. Syst. Man Cybernet. 24, 1994, 246-267.
41. A. Sha'ashua and S. Ullman, Structural saliency: The detection of globally salient structures using a locally connected network, in Proceedings, ICCV'88, 1988, pp. 321-327.
42. L. Stark and K. Bowyer, Generic recognition through qualitative reasoning about 3-D shape and object function, in Proceedings, CVPR '91, 1991, pp. 251-256.
43. R. Takiyaama and N. Ono, A least square error estimation of the center and radii of concentric arcs, Pattern Recognit. Lett. 10, 1989, 237-242.
44. M. Wertheimer, Untersuchungen zur Lehe von der Gestalt II, in Psychologische Forschung, Vol. 4, pp. 301-350, 1923; translated as: Principles of perceptual organization, in Readings in Perception (D. Beardslee and M. Wertheimer, Eds.), pp. 115-135, Van Nostrand, Princeton, NJ, 1958.
45. M. Wertheimer, Untersuchungen zur Lehe von der Gestalt II, in Psychologische Forschung, Vol. 4, pp. 301-350, 1923; translated as: Principles of perceptual organization, in Readings in Perception (D. Beardslee and M. Wertheimer, Eds.), pp. 115-135, Van Nostrand, Princeton, NJ, 1958.
46. A. P. Witkin and M. Tenenbaum, On the role of structure in vision, in Human and Machine Vision (Beck, Hope, and Rosenfeld, Eds.), pp. 481-543, Academic Press, New York, 1983.
47. M. Zerroug and R. Nevatia, Segmentation and recovery of SHGCs from a real intensity image, in Lecture Notes in Computer Science, Computer Vision - ECCV'94 (J.-O. Eklundh, Ed.), vol. 800, 1994, 319-330, Springer-Verlag, New York, 1994.
48. S. W. Zucker, Computational and psychophysical experiments in grouping: Early orientation selection, in Human and Machine Vision (Beck, Hope, and Rosenfeld, Eds.), pp. 545-567, Academic Press, New York, 1983.