Finding folds: on the appearance and identification of occlusion

A natural sequel to edge detection is the interpretation of edges. This interpretation can provide useful information to various computer vision processes, including recognition, reconstruction, and tracking. In this paper we consider the problem of identifying occlusion edges in a single image. We examine the appearance of occlusion edges under variable illumination, both analytically and empirically, and find that the pattern of shading in the neighborhood of occlusion edges is a stable feature. Finally, we derive a filter for detecting occlusion and present the results of its application.

[1]  Andrew P. Within Intensity-based edge classification , 1982, AAAI 1982.

[2]  Steven W. Zucker,et al.  Folds and cuts: how shading flows into edges , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[3]  Jan J. Koenderink,et al.  Local features of smooth shapes: ridges and courses , 1993, Optics & Photonics.

[4]  David W. Jacobs,et al.  In search of illumination invariants , 2001, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[5]  Paul Smith,et al.  Edge Tracking for Motion Segmentation and Depth Ordering , 1999, BMVC.

[6]  Andrew P. Witkin Intensity-Based Edge Classification , 1982, AAAI.

[7]  Steven W. Zucker,et al.  A Three-Dimensional Edge Operator , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  R. Weale Vision. A Computational Investigation Into the Human Representation and Processing of Visual Information. David Marr , 1983 .

[9]  Alan L. Yuille,et al.  Fundamental bounds on edge detection: an information theoretic evaluation of different edge cues , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[10]  Olivier D. Faugeras,et al.  Using Extremal Boundaries for 3-D Object Modeling , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Jan J. Koenderink,et al.  Two-dimensional curvature operators , 1988 .

[12]  David A. Forsyth,et al.  Reflections on Shading , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  M. Loève Probability theory : foundations, random sequences , 1955 .

[14]  H. Whitney On Singularities of Mappings of Euclidean Spaces. I. Mappings of the Plane Into the Plane , 1955 .

[15]  William T. Freeman,et al.  The generic viewpoint assumption in a framework for visual perception , 1994, Nature.

[16]  Jan J. Koenderink,et al.  Solid shape , 1990 .

[17]  Richard Szeliski,et al.  Robust Shape Recovery from Occluding Contours Using a Linear Smoother , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[18]  Fredrik Kahl,et al.  Motion estimation in image sequences using the deformation of apparent contours , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[19]  Marcel Worring,et al.  Digital curvature estimation , 1993 .

[20]  Josef Kittler,et al.  Pattern recognition : a statistical approach , 1982 .

[21]  Alan L. Yuille,et al.  The Generic Viewpoint Assumption and Planar Bias , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Josef Kittler,et al.  Edge-Labeling Using Dictionary-Based Relaxation , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Robert A. Hummel,et al.  Feature detection using basis functions , 1979 .

[24]  Steven W. Zucker,et al.  Shadows and shading flow fields , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[25]  Katsushi Ikeuchi,et al.  Numerical Shape from Shading and Occluding Boundaries , 1981, Artif. Intell..

[26]  Sudeep Sarkar,et al.  Robust Visual Method for Assessing the Relative Performance of Edge-Detection Algorithms , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  J J Koenderink,et al.  What Does the Occluding Contour Tell Us about Solid Shape? , 1984, Perception.

[28]  Steven W. Zucker,et al.  Logical/Linear Operators for Image Curves , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[29]  J. P. Dufour,et al.  Families de courbes planes differentiables , 1983 .

[30]  Steven W. Zucker,et al.  What is a light source? , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[31]  Berthold K. P. Horn Understanding Image Intensities , 1977, Artif. Intell..

[32]  Steven W. Zucker,et al.  How Folds Cut a Scene , 2001, IWVF.

[33]  Naoki Asada,et al.  Seeing Behind the Scene: Analysis of Photometric Properties of Occluding Edges by the Reversed Projection Blurring Model , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  David J. Kriegman,et al.  Invariant-based recognition of complex curved 3D objects from image contours , 1995, Proceedings of IEEE International Conference on Computer Vision.

[35]  Joachim H. Rieger,et al.  The Geometry of View Space of Opaque Objects Bounded by Smooth Surfaces , 1990, Artif. Intell..