Object Discrimination Based on Depth-From-Occlusion
Abstract
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 close 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. In order to discriminate objects in the visual world, the nervous system must solve two fundamental problems: binding and segmentation. The binding problem (Barlow, 1981) addresses how the attributes of an object shape, color, motion, depth are linked to create an individual object. Segmentation deal with the converse problem of how separate objects are distinguished.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1991
- Accession Number
- ADA248104
Entities
People
- Leif H. Finkel
- Paul Sajda
Organizations
- University of Pennsylvania