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Vision Systems for a Natural Human Environment

Ziel

The aim of INSIGHT II is to improve our understanding of vision at the computational level, that is, to identify the representations to be used and the algorithms to compute them for general-purpose vision systems operating in a fluctuating natural environment.
The site of convergence of luminance, motion and texture cues specifying shape in the primate brain has been established.

New insights into the receptive field structure of higher order visual neurons and on the integration of visual and eye movement signals in the primate brain has been achieved.

On the psychophysical side, a new technique has been developed for the measurement of subjects' perception of surfaces. A wealth of new data on the estimation by humans of surface position, orientation and curvature specified by disparity, motion, luminance, texture and other cues has been obtained.

On the computational side, a new theory has been developed on the recovery of surfaces from the structure of the disparity field.

In computer vision, mathematical theory, implementation and experimentation have been combined to estimate optic flow and its use for recovering object 3-dimensional structure and 3-dimensional motion.
APPROACH AND METHODS

Using the results of a previous action (INSIGHT, 3001) as a guide, a number of key areas have been identified, mainly in middle-level vision, where rapid progress can be expected. These areas include the measurement of optic flow, cue integration, the task-dependent use of optic flow, and surface and object representation. These five topics are approached from a multidisciplinary point of view combining psychophysics and neurophysiology in studying biological visual system in primates, and computer science in studying computer vision. While psychophysics studies human or primate performance and conjectures about underlying mechanisms, physiology measures these mechanisms directly. The strategies employed by the most successful computer (the primate brain) will thus be confronted with those used in computer vision to solve similar problems.

POTENTIAL

The vision knowledge gained from these fundamental studies will give firm ground to more applied projects in which vision is used to guide robots or recognise patterns.

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Koordinator

KATHOLIEKE UNIVERSITEIT LEUVEN
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TERVUURSEVEST, 101
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Letzte Aktualisierung: 17 Juni 1994

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Permalink: https://cordis.europa.eu/project/id/6019/de

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