Representation and extraction of image feature associated with maneuvering affordance

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 Fourier images. For extracting not-yet-identified self-similar pattern, noise level is estimated based on probabilistic complexity analysis. The detectability of affordance patterns has been verified through experimental studies.