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Computer Engineering ›› 2020, Vol. 46 ›› Issue (3): 254-260,266. doi: 10.19678/j.issn.1000-3428.0054295

• Graphics and Image Processing • Previous Articles     Next Articles

Performance Evaluation for Moving Target Tracking Algorithm Based on Orthogonal Test

XI Runping1,2,3, XUE Shaohui1,2,3   

  1. 1. School of Computer Science, Northwestern Polytechnical University, Xi'an 710129, China;
    2. National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, Xi'an 710129, China;
    3. Shaanxi Provincial Key Laboratory of Speech and Image Information Processing, Xi'an 710129, China
  • Received:2019-03-19 Revised:2019-04-23 Published:2019-05-16

基于正交试验的运动目标跟踪算法性能评价

郗润平1,2,3, 薛少辉1,2,3   

  1. 1. 西北工业大学 计算机学院, 西安 710129;
    2. 空天地海一体化大数据应用技术国家工程实验室, 西安 710129;
    3. 陕西省语音与图像信息处理重点实验室, 西安 710129
  • 作者简介:郗润平(1971-),男,副教授、博士,主研方向为图形图像处理、计算机视觉;薛少辉(通信作者),硕士研究生。
  • 基金资助:
    国家自然科学基金"基于生物视觉的无人机群多源图像目标协同检测方法研究"(61572405);国家高技术研究发展计划"全景互动关键技术与示范系统主题项目"(2015AA016400)。

Abstract: The performance evaluation of existing moving target tracking algorithms has many drawbacks,such as massive amount of data,redundant tests and insufficient consideration on algorithm performance under multifactor situation.Therefore,this paper proposes a performance evaluation method for moving target tracking algorithm based on orthogonal test.After a full analysis on the factors and levels that affect algorithm performance,the dataset of orthogonal test is built and then used for algorithm performance test.The data results are analyzed by the range analysis method,so as to obtain the relationship between the factors that affect the algorithm,as well as the combination of factor levels when the algorithm performance is good.Experimental results show that the proposed method can evaluate the performance of the moving target tracking algorithm in a comprehensive and effective way.Besides,this method can reduce the number of tests and data volume,and provide reference for the performance evaluation of other image processing algorithms.

Key words: orthogonal test, target tracking, evaluation index, multifactor combination, range analysis method

摘要: 针对目前运动目标跟踪算法性能评价中测试数据量大、试验次数多以及未充分考虑多因素组合场景下的算法性能表现等问题,提出一种基于正交试验的运动目标跟踪算法性能评价方法。分析影响算法性能的因素和水平,构建正交试验数据集,通过该数据集测试算法性能并利用极差分析法分析数据结果,以得到各影响因素间的强弱关系以及算法性能表现较好时的因素水平组合方式。分析结果表明,该方法能够全面、有效地评估运动目标跟踪算法的性能,减少测试次数和数据量,并为其他图像处理算法的性能评估提供参考。

关键词: 正交试验, 目标跟踪, 评价指标, 多因素组合, 极差分析法

CLC Number: