Recognizing heuman actions based on motion information and SVM
Recognizing heuman actions based on motion information and SVM
复制标题
基于运动信息和SVM的Heuman动作识别
DOI：
10.1049/cp:20060648
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
Chris Bailey
中科院分区：
文献类型：
--
作者：
Hongying Meng;Nick E. Pears;Chris Bailey
在本文中，我们提出了一个新的系统，人类行为识别，以期在安全系统，人机通信和智能环境中的应用。我们的系统是基于非常简单的功能，以实现高速识别在现实世界中的应用。我们选择了三种主要技术来构建一个可以实时工作的系统。首先，我们选择运动历史图像和相关特征。其次，我们使用一个模板匹配的方法，而不是状态空间的方法，需要昂贵的建模过程，最后，我们使用线性分类器支持向量机（SVM）的快速分类。实验结果表明，该系统在智能环境等实时嵌入式应用中能够取得较好的人体动作识别效果
In this paper, we propose a new system for human action recognition with a view to applications in security systems, man-machine communications and intelligent environments. Our system is based on very simple features in order to achieve high-speed recognition in real-world applications. We have chosen three main techniques to build a system that can work in real-time. Firstly, we choose motion history images and related features. Secondly, we use a template matching methods instead of state-space methods that need expensive modelling processes; finally, we use linear classifier support vector machine (SVM) for fast classification. Experimental results show that this system can achieve good performance in human action recognition in realtime embedded applications, such as intelligent environments