激光与光电子学进展, 2018, 55 (1): 011010, 网络出版: 2018-09-10   

基于判别协作表征分类器的人体行为识别 下载: 940次

Human Action Recognition Based on Discriminative Collaborative Representation Classifier
昝宝锋 1,*孔军 1,2蒋敏 1
作者单位
1 江南大学物联网工程学院, 江苏 无锡 214122
2 新疆大学电气工程学院, 新疆 乌鲁木齐 830047
摘要
为了解决协作表征分类器(CRC)对相似样本误分类概率高的问题,提出一种判别协作表征分类器(DCRC)。该分类器考虑了所有训练样本和每一类样本对协作表征系数的影响,得到判别性强的协作表征系数,提升了对相似样本的判别性。基于DCRC进行人体行为识别研究。首先用深度运动映射图(DMMs)提取深度动作序列特征,得到DMMs特征描述子,然后利用DCRC对特征描述子进行协作表征编码,最后利用新的判别规则进行分类识别。在人体行为识别数据集上的实验结果表明,DCRC对相似动作具有一定的判别性,且识别精度优于现有的方法。
Abstract
In order to solve the problem of high probability of misclassification for similar samples of the collaborative representation classifier (CRC), we propose a discriminative CRC (DCRC), which takes the effect of all training samples and each class of training samples on the collaborative representation coefficient into account. The coefficient obtained has strong discrimination and can improve the discriminability of the similar samples. Human action recognition is conducted based on DCRC. We first extract the features of depth action sequence via depth motion maps (DMMs). Then, we use DCRC to encode the DMMs features and perform classification and recognition by new classification rules. Experimental results on the human action recognition datasets show that the DCRC has certain discriminative properties for similar actions, and the recognition accuracy is superior to some existed methods.

昝宝锋, 孔军, 蒋敏. 基于判别协作表征分类器的人体行为识别[J]. 激光与光电子学进展, 2018, 55(1): 011010. Zan Baofeng, Kong Jun, Jiang Min. Human Action Recognition Based on Discriminative Collaborative Representation Classifier[J]. Laser & Optoelectronics Progress, 2018, 55(1): 011010.

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