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Solitary oldies abnormal action recognition based on MEI

机译:基于MEI的孤老异常动作识别

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This paper presents a new method for identifying the abnormal action of the solitary oldies which is based on video sequence. First, we use the background subtraction and morphological filtering technology to extract the moving human contour. Then, we extract the motion energy image (MEI) of the moving body target, which is followed by extracting the Hu moments feature of human motion energy image extracted. At last, we classify and identify the abnormal action by using Bayesian classifier. Experiments demonstrate that the proposed recognition method is simple and practical. It achieves the correct recognition rate of daily behavior more than 92%. This method can also well identify the falling action, its recognition result is more ideal, and has some great practical value.
机译:本文提出了一种基于视频序列的孤立孤儿异常行为识别新方法。首先,我们使用背景减法和形态滤波技术提取运动中的人的轮廓。然后,我们提取运动物体目标的运动能量图像(MEI),然后提取所提取的人体运动能量图像的Hu矩特征。最后,利用贝叶斯分类器对异常行为进行分类和识别。实验表明,该识别方法简单实用。它对日常行为的正确识别率超过92%。该方法还可以很好地识别跌落动作,其识别结果更加理想,具有一定的实用价值。

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