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COMBINING MULTI-CLASS MAXIMUM MARGIN CLASSIFICATION WITH LINEAR DISCRIMINANT ANALYSIS FOR HUMAN ACTION RECOGNITION

机译:结合多级最大保证金分类,对人类行动认可线性判别分析

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摘要

In this paper, a new multi-class classification method is proposed and evaluated in the problem of human action recognition in unconstrained environments. The proposed method exploits both the maximum margin property of multi-class Support Vector Machines and Linear Discriminant Analysis-based discrimination. Experiments indicate that by exploiting such discriminant information in a multi-class maximum margin framework, classification performance can be enhanced, leading to state-of-the-art performance in human action recognition.
机译:本文提出了一种新的多级分类方法,并在无约束环境中的人类行动识别问题中评估。该方法利用多级支持向量机和基于线性判别分析的歧视的最大边缘特性。实验表明,通过利用在多级最大保证金框架中的这种判别信息,可以提高分类性能,从而导致人类行动识别中的最先进的性能。

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