Vision system based on shifted fovea multiresolution retinotopologies

Abstract

In this paper, the authors present a foveal active vision system. It is capable of moving and fixating the fovea to any region of a scene, detecting its most relevant areas to extract certain features of these regions of interest. The system conducts a segmentation of the image, detects the possible existing objects in the scene, obtains hierarchically a set of features for each detected object-centroid, area, bounding box and grey level and extracts the corners of the object contained in the fovea. This system is going to be integrated in an autonomous mobile agent, so it is important to process each object in the optimal resolution level to minimise computational load and time requirements. The most important novelty of the system is the use of reconfigurable shifted fovea retinotopologies, also including a new algorithm capable of obtaining a curvature function by means of local histograms of the contour chain code to reliably calculate the stable corners of the contour of the objects.