When Shadows Become Interreflections

Shadows and interreflections are present in all real scenes and provide a rich set of photometric cues for vision. In this paper, we show how shadows and interreflections are intrinsically related. Shadows tend to occur in those parts of a scene in which interreflections have the largest gain. We provide several basic results concerning this relationship in terms of the interreflection modes of a scene. We show that for a given scene, the interreflection mode having the largest gain is a physically realizable radiance function. We derive bounds on the gain of this mode and discuss how this mode is related to shadows. We analyze how well an n-bounce model of interreflections approximates an infinite-bounce model and how shadows affect this approximation. Finally, we introduce a novel method for inferring surface color in a uni-chromatic scene. The method is based on the relative contrast of the scene in different color channels.

[1]  John K. Tsotsos,et al.  Ambient illumination and the determination of material changes. , 1986, Journal of the Optical Society of America. A, Optics and image science.

[2]  Stuart Anstis,et al.  VISUAL ADAPTATION TO A NEGATIVE, BRIGHTNESS-REVERSED WORLD: SOME PRELIMINARY OBSERVATIONS , 2002 .

[3]  S. Zucker,et al.  Shape-from-shading on a cloudy day , 1994 .

[4]  David A. Forsyth,et al.  Shading primitives: finding folds and shallow grooves , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

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

[6]  D. Spencer,et al.  The photic field , 1981 .

[7]  J. M. Rubin,et al.  Color vision and image intensities: When are changes material? , 1982, Biological Cybernetics.

[8]  V. Leitáo,et al.  Computer Graphics: Principles and Practice , 1995 .

[9]  David J. Kriegman,et al.  The Bas-Relief Ambiguity , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[10]  Takeo Kanade,et al.  Shape from interreflections , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[11]  Mark S. Drew,et al.  Color Space Analysis of Mutual Illumination , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  David L. Waltz,et al.  Understanding Line drawings of Scenes with Shadows , 1975 .

[13]  Anya C. Hurlbert,et al.  Discounting the color of mutual illumination: A 3-d-shape-induced color phenomenon , 1996 .

[14]  Daniel R. Baum,et al.  Improving radiosity solutions through the use of analytically determined form-factors , 1989, SIGGRAPH.

[15]  S. Shafer Shadows and Silhouettes in Computer Vision , 1985 .

[16]  David J. Kriegman,et al.  The Bas-Relief Ambiguity , 2004, International Journal of Computer Vision.

[17]  M. Carter Computer graphics: Principles and practice , 1997 .

[18]  J. Koenderink,et al.  Geometrical modes as a general method to treat diffuse interreflections in radiometry , 1983 .

[19]  A. Gilchrist,et al.  Perception of Lightness and Illumination in a World of One Reflectance , 1984, Perception.

[20]  Domina Eberle Spencer,et al.  Interflections and color , 1951 .

[21]  M. Pinar Mengüç,et al.  Thermal Radiation Heat Transfer , 2020 .

[22]  Mark S. Drew,et al.  Color constancy from mutual reflection , 1991, International Journal of Computer Vision.

[23]  Shree K. Nayar,et al.  Seeing Beyond Lambert's Law , 1994, ECCV.