Representation and Extraction of Multi-Scale Image Feature Associated with Maneuvering Affordance

Abstract

A detection scheme is presented for maneuvering affordance in noisy imagery. Under the assumption that image features to be observed are generated as fractal attractors induced by mental maneuvering process, environment features are represented in directional scale images. For eliminating background noise in this sampling process, pixelwise filter is designed based on probabilistic complexity analysis. The detectability of affordance patterns has been verified through experimental studies.