文献类型：会议论文

英文题名：Fish Target Detection and Speed Estimation Method based on Computer Vision

作者：Zhang, Lanyue[1,2,3]; Zhai, Guilin[1,2,3]; Hu, Bo[1,2,3]; Qiao, Zhi[1,2,3]; Zhang, Peizhen[4]

机构：[1] Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin, 150001, China; [2] Key Laboratory of Marine Information Acquisition and Security[Harbin Engineering University], Ministry of Industry and Information Technology, Harbin, 150001, China; [3] College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin, 150001, China; [4] College of Electronic and Information Engineering, Guangdong Ocean University, Zhanjiang, China

会议论文集：2023 IEEE 6th International Conference on Electronic Information and Communication Technology, ICEICT 2023

会议日期：July 21, 2023 - July 24, 2023

会议地点：Qingdao, China

语种：英文

外文关键词：Binocular vision - Binoculars - Computer vision - Deep learning - Target tracking - Underwater imaging

外文摘要：Taking the monitoring of fish status in aquaculture cages as the research background, the survival status of fish is assessed through the estimation of fish swimming speed, and the Yolov3 target detection algorithm and Deep-sort multi-target tracking algorithm based on deep learning are studied to achieve fish target detection. And trajectory tracking, the imaging model of the underwater binocular camera is established, the three-dimensional coordinates of the underwater fish target image point are obtained, and the speed estimation of the fish target is realized on the basis of the continuous tracking of the fish target. Compared with the other algorithms of fish body separation, the research results show that the method proposed in this paper has an average detection accuracy of 96.16% for underwater fish targets, and the average relative error of fish movement speed estimation under natural lighting conditions is 1.60%. ? 2023 IEEE.