On human activity recognition in video sequences

C. M. Sharma, A. Kushwaha, S. Nigam, A. Khare
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引用次数: 10

Abstract

In this paper, we describe a novel template matching based approach for recognition of different human activities in a video sequence. We model the background in the scene using a simple statistical model and extract the foreground objects present in a scene. The matching templates are constructed using the motion history images (MHI) and spatial silhouettes for recognizing activities like walking, standing, bending, sleeping and jogging in a video sequence. Experimental results demonstrate that the proposed method can recognize these activities accurately for standard KTH database as well as for our own database.
视频序列中的人体活动识别
在本文中,我们描述了一种新的基于模板匹配的方法来识别视频序列中不同的人类活动。我们使用简单的统计模型对场景中的背景进行建模,并提取场景中存在的前景对象。匹配模板使用运动历史图像(MHI)和空间轮廓来识别视频序列中的行走、站立、弯曲、睡眠和慢跑等活动。实验结果表明,该方法对标准KTH数据库和我们自己的数据库都能准确识别这些活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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