Human Gait Recognition using Deep Convolutional Neural Network

P. Nithyakani, A. Shanthini, Godwin Ponsam
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引用次数: 11

Abstract

A human acknowledgment and recognizable proof is viewed these days as an essential field of research. The most unique parts of human are the ear, odor, heartbeat, voice, the iris, periocular portion of eye, fingerprint, gait, sweat, face, etc,. Without the human interaction to identify a person is quite challenging with low resolution images. Gait recognition is one of the biometric technology which can be used to identify people without their knowledge. The proposed system uses Deep Convolutional Neural Network to extract the gait features of a person by training the neural network architecture with Gait Energy Image.
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基于深度卷积神经网络的人体步态识别
如今,人类的承认和可识别的证据被视为一个重要的研究领域。人类最独特的部分是耳朵、气味、心跳、声音、虹膜、眼周部分、指纹、步态、汗水、面部等。在没有人类互动的情况下,用低分辨率的图像识别一个人是相当具有挑战性的。步态识别是一种生物特征识别技术,可以在人不知情的情况下对其进行识别。该系统采用深度卷积神经网络,通过步态能量图像训练神经网络结构,提取人的步态特征。
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