A Survey on Automated Human Action Recognition Using Multi view Feature

S. Ashwini, Varalatchoumy
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Abstract

— Recognizing the human action plays a significant role in surveillance cameras. Usually cameras are situated at distant place and convey actions in form of signals at one particular place. This paper presents a framework for recognizing a sequence of actions based on multi-view video data. To depict various actions activities performed in various perspectives, view-invariant feature is being used. The features of multi-view are extracted from various temporal scales, which are demonstrated using global spatial-temporal distribution. The proposed system performs is designed to work on cross tested datasets wherein the system doesn’t require retraining for same scenario that occurs multiple times.
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基于多视图特征的人体动作自动识别研究进展
-识别人的行为在监控摄像机中起着重要作用。摄像机通常安装在较远的地方,在一个特定的地方以信号的形式传达动作。本文提出了一种基于多视点视频数据的动作序列识别框架。为了描述在不同透视图中执行的各种操作活动,使用了视图不变特性。从不同的时间尺度提取多视图特征,并利用全局时空分布对其进行论证。所提出的系统执行设计用于交叉测试的数据集,其中系统不需要对多次发生的相同场景进行重新训练。
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