Visual tracking for underwater sea cucumber via correlation filters

IF 2.2 2区农林科学 Q2 AGRICULTURAL ENGINEERING

International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI:10.25165/j.ijabe.20231603.4503

Honglei Wei, Xiangzhi Kong, Xianyi Zhai, Qiang Tong, Guibing Pang

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引用次数: 0

Abstract

One of the essential techniques for using underwater robots to fish sea cucumbers is that the robots must track sea cucumbers using computer vision technology. Tracking underwater targets is a challenging task due to suspension, water absorption, and light scattering. This study proposed a simple but effective algorithm for sea cucumber tracking based on Kernelized Correlation Filters (KCF) framework. This method tracked the head and tail of the sea cucumber respectively and calculated the scale change according to the distance between the head and tail. The KCF method was improved on three strategies. First of all, the target was searched at the predicted position to improve accuracy. Secondly, an adaptive learning rate updating method based on the detection score of each frame was proposed. Finally, the adaptive size of the histogram of the oriented gradient (HOG) feature was used to balance the accuracy and efficiency. Experimental results showed that the algorithm had good tracking performance. Keywords: visual tracking, correlation filters, kernelized correlation filters, sea cucumber, scale estimation, underwater DOI: 10.25165/j.ijabe.20231603.4503 Citation: Wei H L, Kong X Z, Zhai X Y, Tong Q, Pang G B. Visual tracking for underwater sea cucumber via correlation filters. Int J Agric & Biol Eng, 2023; 16(3): 16(3): 247–253.

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基于相关滤波器的水下海参视觉跟踪

利用计算机视觉技术对海参进行跟踪是水下机器人捕捞海参的关键技术之一。由于悬浮、吸水、光散射等问题，跟踪水下目标是一项具有挑战性的任务。提出了一种简单有效的基于核相关滤波器(KCF)框架的海参跟踪算法。该方法分别对海参的头部和尾部进行跟踪，根据头部和尾部之间的距离计算尺度变化。通过三种策略对KCF方法进行了改进。首先在预测位置对目标进行搜索，提高搜索精度;其次，提出了一种基于每帧检测分数的自适应学习率更新方法;最后，利用定向梯度(HOG)特征直方图的自适应大小来平衡精度和效率。实验结果表明，该算法具有良好的跟踪性能。关键词:视觉跟踪，相关滤波器，核化相关滤波器，海参，尺度估计，水下[DOI: 10.25165/ j.j ijabe.20231603.4503]引用本文:魏海龙，孔祥志，翟晓燕，佟强，庞国斌。基于相关滤波器的水下海参视觉跟踪。农业与生物工程学报，2023;16(3): 16(3): 247-253。

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来源期刊

International Journal of Agricultural and Biological Engineering AGRICULTURAL ENGINEERING-

CiteScore

4.30

自引率

12.50%

发文量

审稿时长

24 weeks

期刊介绍： International Journal of Agricultural and Biological Engineering (IJABE, https://www.ijabe.org) is a peer reviewed open access international journal. IJABE, started in 2008, is a joint publication co-sponsored by US-based Association of Agricultural, Biological and Food Engineers (AOCABFE) and China-based Chinese Society of Agricultural Engineering (CSAE). The ISSN 1934-6344 and eISSN 1934-6352 numbers for both print and online IJABE have been registered in US. Now, Int. J. Agric. & Biol. Eng (IJABE) is published in both online and print version by Chinese Academy of Agricultural Engineering.