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Features analysis and Fuzzy-SVM classification for tracking players in water polo

机译:水球运动员追踪的特征分析和模糊支持向量机分类

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摘要

This paper presents a novel approach for detection and tracking humans in water. Uniqueness of the tracked objects has been defined after analysis of standard color models. Based on the analysis results, YCbCr is proposed as the best color model for targeted application. Furthermore, relation of Cb and Cr components for different categories of targeted objects (object parts) were analyzed and used as features that can be used by classifier. Fuzzy-SVM classifier is proposed as the best solution for particular domain of problems. Unlike other Fuzzy-SVM methods, presented method is focused on fuzzy logic and applies binary SVM only in special situations when classification of input data is uncertain. In order to test and evaluate hypothesis, proposed method was compared to standard classification methods. Experimental results demonstrated validity and efficiency of the proposed approach.
机译:本文提出了一种新的方法来检测和跟踪水中的人类。在分析标准颜色模型后,已定义了跟踪对象的唯一性。根据分析结果,提出YCbCr作为针对目标应用的最佳颜色模型。此外,分析了不同类别的目标对象(对象部分)的Cb和Cr成分之间的关​​系,并将其用作可用于分类器的特征。提出模糊-SVM分类器作为针对特定问题领域的最佳解决方案。与其他Fuzzy-SVM方法不同,本文提出的方法着重于模糊逻辑,仅在不确定输入数据分类的特殊情况下才应用二进制SVM。为了检验和评估假设,将提出的方法与标准分类方法进行了比较。实验结果证明了该方法的有效性和有效性。

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