Human image understanding: Recent research and a theory
I Biederman - Computer vision, graphics, and image processing, 1985 - Elsevier
The perceptual recognition of objects is conceptualized to be a process in which the image
of the input is segmented at regions of deep concavity into simple volumetric components,
such as blocks, cylinders, wedges, and cones. The fundamental assumption of the proposed
theory, recognition-by-components (RBC), is that a modest set of components [N probably≤
36] can be derived from contrasts of five readily detectable properties of edges in a 2-
dimensional image: curvature, collinearity, symmetry, parallelism, and cotermination. The …
of the input is segmented at regions of deep concavity into simple volumetric components,
such as blocks, cylinders, wedges, and cones. The fundamental assumption of the proposed
theory, recognition-by-components (RBC), is that a modest set of components [N probably≤
36] can be derived from contrasts of five readily detectable properties of edges in a 2-
dimensional image: curvature, collinearity, symmetry, parallelism, and cotermination. The …
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