A Computational Model for Visual Selection

摘要

We propose a computational model for detecting and localizing instances from an object class in static gray-level images. We divide detection into visual selection and final classification, concentrating on the former: dras- tically reducing the number of candidate regions the require further, usually more intensive, processing, but with a minimum of computation ad missed detections. Bottom-up processing is based on local groupings of edge fragments constrained by loose geometrical relationships. They have no a priori semantic or geometric interpretation.