A bio-inspired connectionist approach for motion description through sequences of images

Abstract

This paper presents a bio-inspired connectionist approach for motion description through sequences of images. First, this approach is based on the architecture of oriented columns and the strong local and distributed interactions of the neurons in the primary visual cortex (V1). Secondly, in the integration and combination of their responses in the middle temporal area (MT). I propose an architecture in two layers : a causal spatio-temporal filtering (CSTF) of Gabor-like type which captures the oriented contrast and a mechanism of antagonist inhibitions (MAI) which estimates the motion. The first layer estimates the local orientation and speed, the second layer classifies the motion (global response) and both describe the motion and the pursuit trajectory. This architecture has been evaluated on sequences of natural and synthetic images. © Springer-Verlag Berlin Heidelberg 2007.