Abstract
Objective and effective algorithm performance evaluation results are an important basis for the selection of tracking algorithms. Problems in the existing performance evaluation of moving target tracking algorithms include an enlarge number of trials, and in particular, failure to consider the influence of algorithm performance on the multifactor combination scenario. This study proposes a method based on the orthogonal test to evaluate algorithms. First, the factors and levels of the tracking algorithm are analyzed, and an orthogonal test dataset is constructed by using an orthogonal table. Second, the experiments of the performance evaluation are arranged with the dataset and the results are analyzed via range analysis. Finally, evaluation results show that the strong–weak sequence of factors affect the performance of the algorithm and the combination of levels form the factors that can achieve enhanced algorithm performance. Experimental results show that the proposed method can evaluate algorithms comprehensively, objectively, and effectively with decreased test and data volume.
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Acknowledgement
This work is supported by the National Natural Science Foundation of China (No. 61572405) and the National High Technology Research and Development Program of China (863 Program) (No. 2015AA016402).
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Xi, R., Xue, S., Han, Q., Chen, J. (2019). An Approach to the Applicability Evaluation of Moving Target Tracking Algorithm. In: Lin, Z., et al. Pattern Recognition and Computer Vision. PRCV 2019. Lecture Notes in Computer Science(), vol 11859. Springer, Cham. https://doi.org/10.1007/978-3-030-31726-3_4
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DOI: https://doi.org/10.1007/978-3-030-31726-3_4
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