Abstract
We measured pictorial relief for a series of pictures of a smooth solid object. The scene was geometrically identical (i.e., the perspective of the same 3D scene) for all pictures, the rendering different. Some of the pictures were monochrome full scale photographs taken under different illuminations of the scene. We also included a silhouette (uniform black on uniform white) and a “cartoon” style rendering (visual contour and key linear features rendered in thin black line on a uniform white ground). Two subjects were naive and started with the silhouette, next did the cartoon, finally the full scale photographs. Another subject had seen the object and did the experiment in the opposite sequence. The silhouette rendering is impoverished,but has considerable relief with much of the basic shape. The cartoon rendering yields well developed pictorial relief, even in the naive subjects. Shading adds only small local details, but different illuminations produce significant alterations of relief. We conclude that shape constancy under changes in illumination rules throughout, but that the (small) deviations from true constancy reveal the effect of cues such as shading in a natural setting. Such a “perturbation analysis” appears more promising than either stimulus reduction or cue conflict paradigms.
An earlier version of this paper was published in Perception, volume 5, 1996. This paper is included in this volume by kind permission of Pion Ltd. Jan Koenderink is supported by the Human Frontiers Science Program. Andrea van Doorn is supported by the Netherlands Organization for Scientific Research (NWO). Chris Christou is supported by the ESPRIT Basic Research Action INSIGHT of the European Commission. Joe Lappin visited Utrecht for two months and was supported by the Human Frontiers Science Program.
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© 1996 Springer-Verlag Berlin Heidelberg
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Koenderink, J.J., van Doorn, A.J., Christou, C., Lappin, J.S. (1996). Shape constancy in pictorial relief. In: Ponce, J., Zisserman, A., Hebert, M. (eds) Object Representation in Computer Vision II. ORCV 1996. Lecture Notes in Computer Science, vol 1144. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61750-7_27
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DOI: https://doi.org/10.1007/3-540-61750-7_27
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