Abstract
Abstract : Substantial progress has been made on an empirical and theoretical analysis of human image understanding. The theory, termed Recognition-by-Components (RBC), holds that the perceptual recognition of objects is a process in which the image of the input is segmented at regions of deep concavity into simple volumetric components. These components can be derived from properties of the two dimensional image that are invariant over viewing position and image quality, such as collinearity and symmetry. Experimental results support the sufficiency of RBC in showing efficient speeded recognition of objects missing parts or lacking color and texture. Also confirmed was a prediction derived from RBC that selective contour deletion that bridged concavities and prevented retrieval of the components would render object identification impossible. (Author)
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