Consistent fish tracking via multiple underwater cameras

Abstract

In this paper, the consistent fish tracking strategies have been present for the underwater surveillance system with multiple static cameras in the overlapping field of views (FOV). The discriminative appearance model has been first introduced to distinguish the swimming fish and the background by the superpixel. The centroid coordinate homographic mapping and the Speeded Up Robust Features (SURF) technique have been taken to capture and match the same fish from the perspectives among multiple cameras by a set of strategies. Simulation experiments have shown that the proposed method is less dependent on the exact motion detection of the fish and could perform robustly and stably at a high speed in case of the occlusion and appearance variation under the sea.