Perceptual Models For Computer Vision

Panos A. Ligomenides

doi:10.1117/12.960300

27 March 1989 Perceptual Models For Computer Vision

Panos A. Ligomenides

Proceedings Volume 1002, Intelligent Robots and Computer Vision VII; (1989) https://doi.org/10.1117/12.960300
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States

Abstract

Human perception of resemblance in spatio-temporal patterns y(x; X) is modeled interactively by procedural elastic templates, called "formal description schema - fds_k" models. The identification, representation and quantification of uncertainty-ambiguity in human holistic perception are problems to be resolved by the man-machine interactive modeling of the human faculties of discernment of generic percepts and perceptual organizations, and of assessment of degrees of conformity to these characteristic elastic constraints of a reference k-norm. Underconstrained and often indeterminate visual sensory patterns are, in turn, recognized in real-time by the procedural fds_k-models, which, progressively and accumulatively, assess conformity of sensory patterns to reference k-norms. In this paper we discuss the nature of the formal tolerance-models of conformity, we review our work on the interactive fds_k-modeling of human perception of resemblance for 1D patterns y(x; X), and we examine fuzzy-theoretic aspects of the probabilistic, possibilistic or belief measures of uncertainty in assessing and in predicting conformity to the elastic constraints of a k-norm, in the presence of incomplete or erroneous sensory data.

Citation Download Citation

Panos A. Ligomenides "Perceptual Models For Computer Vision", Proc. SPIE 1002, Intelligent Robots and Computer Vision VII, (27 March 1989); https://doi.org/10.1117/12.960300

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