Multiple fish tracking via Viterbi data association for low-frame-rate underwater camera systems

Non-extractive fish abundance estimation with the aid of visual analysis has drawn increasing attention. Low frame rate and variable illumination in the underwater environment, however, makes conventional tracking methods unreliable. In this paper, a robust multiple fish tracking system for low-frame-rate underwater stereo cameras is proposed. With the result of fish segmentation, a computationally efficient block-matching method is applied to perform successful stereo matching. A multiple-feature matching cost function is utilized to give a simple but effective metric for finding the temporal match of each target. Built upon reliable stereo matching, a multiple-target tracking algorithm via the Viterbi data association is developed to overcome the poor motion continuity of targets. Experimental results show that an accurate underwater live fish tracking result with stereo cameras is achieved.