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[1]刘吉伟,魏鸿磊,裴起潮,等.采用相关滤波的水下海参目标跟踪[J].智能系统学报,2019,14(03):525-532.[doi:10.11992/tis.201711037]
 LIU Jiwei,WEI Honglei,PEI Qichao,et al.Underwater sea cucumber target tracking algorithm based on correlation filtering[J].CAAI Transactions on Intelligent Systems,2019,14(03):525-532.[doi:10.11992/tis.201711037]
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第14卷
期数:
2019年03期
页码:
525-532
栏目:
出版日期:
2019-05-05

文章信息/Info

Title:
Underwater sea cucumber target tracking algorithm based on correlation filtering
作者:
刘吉伟1 魏鸿磊1 裴起潮1 邢利然2
1. 大连工业大学 机械工程与自动化学院, 辽宁 大连 116034;
2. 华北理工大学 机械学院, 河北 唐山 063210
Author(s):
LIU Jiwei1 WEI Honglei1 PEI Qichao1 XING Liran2
1. Institute of Mechanical Engineering and Automation, Dalian Polytechnic University, Dalian 116034, China;
2. College of Mechanical Engineering, North China University of Science and Technology, Tangshan 063210, China
关键词:
视觉追踪循环矩阵离散傅里叶变换核方法岭回归相关滤波器海参采捕尺度估计
Keywords:
visual trackingcirculant matricesdiscrete Fourier transformkernel methodsridge regressioncorrelation filterscapturing sea cucumbersscale estimation
分类号:
TP391
DOI:
10.11992/tis.201711037
摘要:
针对在使用水下机器人采捕时需要实时跟踪定位海参目标的问题,提出了一种基于核相关滤波器的海参目标追踪算法。在初始帧中,根据已知的海参目标的外形特征,将海参整体分为九宫格块,通过边界块与中心块的比较定位海参的两头部位置;使用KCF算法在后续帧中追踪海参两个头部,通过两个模块之间的距离变化来估计海参尺度并计算出目标海参的位置。实验结果表明:在追踪水下海参时,该追踪算法的精确度、运行速度、成功率均高于其他实验算法。
Abstract:
This study proposes a type of sea cucumber target tracking algorithm based on the kernel correlation filter (KCF) to find a solution for real-time tracking while capturing a sea cucumber using an underwater robot. In the initial frame, the image block that contains the target sea cucumber is divided into nine sub-blocks based on the characteristics of the sea cucumber, including its appearance and the positioning of its two heads by comparing the boundary blocks with the central block. Further, the KCF algorithm is used to track the two heads of the sea cucumber in the subsequent frames, estimate the scale, and calculate the location of the sea cucumber based on the distance variation between the two modules. The experimental results exhibit that the accuracy, running speed, and success rate of the tracking algorithm are higher than those of other experimental algorithms.

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备注/Memo

备注/Memo:
收稿日期:2017-11-29。
基金项目:辽宁省自然科学基金项目(2015020027).
作者简介:刘吉伟,男,1993年生,硕士研究生,主要研究方向为机器视觉;魏鸿磊,男,1973年生,副教授,主要研究方向为机器视觉、机电一体化技术。主持省自然科学基金1项,参与国家自然科学基金1项。发表学术论文20余篇,被SCI、EI和ISTP检索10余篇;裴起潮,女,1992年生,硕士研究生,主要研究方向为视觉测量。
通讯作者:魏鸿磊.E-mail:weihl2005@163.com
更新日期/Last Update: 1900-01-01