This paper reviews main approaches to 3D shape perception in both human and computer vision. The approaches are evaluated with respect to their plausibility of generating adequate explanations of human vision. The criterion for plausibility is provided by existing psychophysical results. A new theory of 3D shape perception is then outlined. According to this theory, human perception of shapes critically depends on a priori shape constraints: symmetry and compactness. The role of depth cues is secondary, at best. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Pizlo, Z. (2007). Human perception of 3D shapes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4673 LNCS, pp. 1–12). Springer Verlag. https://doi.org/10.1007/978-3-540-74272-2_1
Mendeley helps you to discover research relevant for your work.