Human Action Recognition Based on Fuzzy Support Vector Machines

Kan Li
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引用次数: 2

Abstract

As human action is uncertain and illegible, a human action recognition method basing on fuzzy support vector machine is presented. Fuzzy support vector machine employs the membership function to solve the unclassifiable areas which happens the traditional SVMs' two-class problems extend to the multi-class problems. the method is evaluated on the Weizmann action dataset and received comparative high correct recognition rate. the experimental results show that our approach has efficient recognition performance.
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基于模糊支持向量机的人体动作识别
针对人体动作具有不确定性和难以辨认性的特点,提出了一种基于模糊支持向量机的人体动作识别方法。模糊支持向量机利用隶属函数来解决传统支持向量机的两类问题扩展到多类问题时出现的不可分类区域。在Weizmann动作数据集上对该方法进行了评估,获得了较高的正确识别率。实验结果表明,该方法具有较好的识别性能。
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