Abstract-Non-extractive fish abundance estimation with the aid of visual analysis has drawn increasing attention. Unstable illumination, ubiquitous noise and low frame rate video capturing in the underwater environment, however, make conventional tracking methods unreliable. In this paper, we present a multiple fish tracking system for low-contrast and low-frame-rate stereo videos with the use of a trawl-based underwater camera system. An automatic fish segmentation algorithm overcomes the low-contrast issues by adopting a histogram backprojection approach on double local-thresholded images to ensure an accurate segmentation on the fish shape boundaries. Built upon a reliable feature-based object matching method, a multiple-target tracking algorithm via a modified Viterbi data association is proposed to overcome the poor motion continuity and frequent entrance/exit of fish targets under low-frame-rate scenarios. In addition, a computationally efficient block-matching approach performs successful stereo matching, which enables an automatic fish-body tail compensation to greatly reduce segmentation error and allows for an accurate fish length measurement. Experimental results show that an effective and reliable tracking performance for multiple live fish with underwater stereo cameras is achieved. Index Terms-fish abundance estimation, low frame rate video, multiple target tracking, stereo imaging, underwater video I. INTRODUCTION ISH abundance estimation [1], which often calls for the use of bottom and midwater trawls, is critically required for the commercially important fish populations in oceanography and fisheries science. However, fish captured by trawls often do not survive, and thus trawl survey methods are inappropriate in some areas where fish stocks are severely depleted. To address these needs, we developed the Cam-trawl [2] to conduct video-based surveys. The absence of the codend allows fish to pass unharmed to the environment after being sampled (captured by cameras). The captured video data provide much
Chuang et al. REF proposed a multiple fish tracking method for low-contrast and low-frame-rate underwater stereo cameras.
Tracking Live Fish from Low-Contrast and Low-Frame-Rate Stereo Videos
IEEE Trans. on Circuits and Systems for Video Technology, vol. 25, no. 1, pp.167-179, Jan. 2015
Computer Science