Panel report: the potential of geons for generic 3-D object recognition
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Sven J. Dickinson | Alex Pentland | Robert Bergevin | Anil K. Jain | Jan-Olof Eklundh | Irving Biederman | Roger Munck-Fairwood | A. Pentland | I. Biederman | R. Bergevin | J. Eklundh | R. Munck-Fairwood
[1] Alain Jacot-Descombes,et al. Probabilistic approach to 3-D inference of geons from a 2-D view , 1992, Defense, Security, and Sensing.
[2] Edward E. Smith,et al. An Invitation to cognitive science , 1997 .
[3] I. Biederman,et al. Chance forced choice recognition memory for identifiable RSVP object pictures , 1994 .
[4] Kevin W. Bowyer,et al. Applications of Artificial Intelligence X: Machine Vision and Robotics , 1992 .
[5] Anil K. Jain,et al. Recognizing geons from superquadrics fitted to range data , 1992, Image Vis. Comput..
[6] A.K. Jain,et al. Obtaining generic parts from range images using a multi-view represen-tation , 1994 .
[7] Sven J. Dickinson,et al. Active Object Recognition Integrating Attention and Viewpoint Control , 1997, Comput. Vis. Image Underst..
[8] Sven J. Dickinson,et al. Qualitative tracking of 3-D objects using active contour networks , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.
[9] Alex Pentland,et al. Generalized implicit functions for computer graphics , 1991, SIGGRAPH.
[10] R. C. Fairwood,et al. Recognition of generic components using logic-program relations of image contours , 1991, Image Vis. Comput..
[11] Sven J. Dickinson,et al. The Use of Geons for Generic 3D Object Recognition , 1993, IJCAI.
[12] Robert Bergevin,et al. Generic object recognition: building coarse 3D descriptions from line drawings , 1989, [1989] Proceedings. Workshop on Interpretation of 3D Scenes.
[13] I. Biederman. Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.
[14] Azriel Rosenfeld,et al. 3-D Shape Recovery Using Distributed Aspect Matching , 1992, IEEE Trans. Pattern Anal. Mach. Intell..
[15] I. Biederman,et al. Viewpoint-dependent mechanisms in visual object recognition: Reply to Tarr and Bülthoff (1995). , 1995 .
[16] Dana H. Ballard,et al. Computer Vision , 1982 .
[17] Martin D. Levine,et al. Recovering parametric geons from multiview range data , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.
[18] Azriel Rosenfeld,et al. Recognition by Functional Parts , 1995, Comput. Vis. Image Underst..
[19] Alex Pentland,et al. Perceptual Organization and the Representation of Natural Form , 1986, Artif. Intell..
[20] James L. McClelland,et al. Information integration in perception and communication , 1996 .
[21] Sven J. Dickinson,et al. A Representation for Qualitative 3-D Object Recognition Integrating Object-Centered and Viewer-Centered Models , 1990 .
[22] Donald D. Hoffman,et al. Parts of recognition , 1984, Cognition.
[23] I. Biederman,et al. Recognizing depth-rotated objects: Evidence and conditions for three-dimensional viewpoint invariance. , 1993 .
[24] I. Biederman,et al. Priming contour-deleted images: Evidence for intermediate representations in visual object recognition , 1991, Cognitive Psychology.
[25] Robert Bergevin,et al. Shape description using geons as a 3D primitives , 1992 .
[26] Zenon W. Pylyshyn,et al. Computational processes in human vision , 1988 .
[27] E. E. Cooper,et al. Recognizing objects with an irregular part , 1995 .
[28] Sven J. Dickinson,et al. The Role of Model-Based Segmentation in the Recovery of Volumetric Parts From Range Data , 1997, IEEE Trans. Pattern Anal. Mach. Intell..
[29] I Biederman,et al. Metric invariance in object recognition: a review and further evidence. , 1992, Canadian journal of psychology.
[30] E Leeuwenberg,et al. From Geons to Structure. A Note on Object Representation , 1994, Perception.
[31] Sven J. Dickinson,et al. A New Approach to Tracking 3D Objects in 2D Image Sequences , 1994, AAAI.
[32] Alex Pentland,et al. Closed-form solutions for physically-based shape modeling and recognition , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[33] J. Hummel,et al. An architecture for rapid, hierarchical structural description , 1996 .
[34] I. Biederman,et al. Surface versus edge-based determinants of visual recognition , 1988, Cognitive Psychology.
[35] Sharath Pankanti,et al. Robust feature detection for 3D object recognition and matching , 1993, Optics & Photonics.
[36] I. Biederman,et al. Dynamic binding in a neural network for shape recognition. , 1992, Psychological review.
[37] Keiji Tanaka,et al. Neuronal selectivities to complex object features in the ventral visual pathway of the macaque cerebral cortex. , 1994, Journal of neurophysiology.
[38] Robert Bergevin,et al. Generic Object Recognition: Building and Matching Coarse Descriptions from Line Drawings , 1993, IEEE Trans. Pattern Anal. Mach. Intell..
[39] Joachim M. Buhmann,et al. Distortion Invariant Object Recognition in the Dynamic Link Architecture , 1993, IEEE Trans. Computers.
[40] Irving Biederman,et al. Human image understanding: Recent research and a theory , 1985, Comput. Vis. Graph. Image Process..
[41] M. Kurbat. Structural Description Theories: Is RBC/JIM a General-Purpose Theory of Human Entry-Level Object Recognition? , 1994, Perception.
[42] PentlandAlex,et al. The Role of Model-Based Segmentation in the Recovery of Volumetric Parts From Range Data , 1997 .
[43] Azriel Rosenfeld,et al. From volumes to views: An approach to 3-D object recognition , 1992, CVGIP Image Underst..
[44] Robert Bergevin,et al. Grouping of Straight Line Segments and Circular Arcs for Scene Analysis , 1995, Research in Computer and Robot Vision.