Multilevel data-fusion for detection of moving objects

Abstract

A knowledge-based vision system called DOORS (Distributed Object-Oriented Recognition System), for obstacle detection and tracking, is presented. It integrates multisensory information sources by adaptively selecting appropriate fusion strategies at the abstraction levels of both physical and virtual sensors. The basic methodology adopted for data representation and processing control has several points in common with object-oriented programming techniques and with blackboard approaches. Some preliminary results are presented for the case of an obstacle moving on a country-road scene.<>