Object discrimination based on depth-from-occlusion

L. H. Finkel, Paul Sajda

We present a model of how objects can be visually discriminated based on the extraction of depth-from-occlusion. Object discrimination requires consideration of both the binding problem and the problem of segmentation. We propose that the visual system binds contours and surfaces by identifying “proto-objects”-compact regions bounded by contours. Proto-objects can then be linked into larger structures. The model is simulated by a system of interconnected neural networks. The networks have biologically motivated architectures and utilize a distributed representation of depth. We present simulations that demonstrate three robust psychophysical properties of the system. The networks are able to stratify multiple occluding objects in a complex scene into separate depth planes. They bind the contours and surfaces of occluded objects (for example, if a tree branch partially occludes the moon, the two “half-moons” are bound into a single object). Finally, the model accounts for human perceptions of illusory contour stimuli.

Received 22 November 1991
Available Online http://www.mitpressjournals.org/doi/pdf/10.1162/neco.1992.4.6.901
Accepted 6 April 1992
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