A unified recognition and stereo vision system for size assessment of fish

This paper presents a unified recognition and stereo vision system which locates objects and determines their distances and sizes given stereo video input. Unlike other such systems, the recognition stage precedes and provides input to stereo processing. Model-based recognition is accomplished in two stages. The first stage seeks feature matches by comparing the absolute orientation, relative orientation and relative length of each image and model segments to find matching chains of segments. The second stage verifies candidate matches by comparing the relative locations of matched image features and corresponding model features. Models are generated semi-automatically from images of the desired objects. In addition to providing distance estimates, feature-based stereo information is used to disambiguate multiple or questionable matches. Although quite general, the system is described in the context of its motivating task of assessing the size of sea-cage salmon non-invasively