Personal Identification by Pedestrians Behavior

E. Kita, Xuanang Feng, Hiroki Shimokubo
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引用次数: 1

Abstract

The recent progress of motion sensor system enables to the personal identification from the human behavior observed from the sensor. Kinect is a motion sensing input device developed by Microsoft for Xbox 360 and Xbox One. The personal identification using the Microsoft Kinect sensor, shortly Kinect, is presented in this study. The use of the Kinect estimates the pedestrian's body size and walk behavior. The human body sizes such as height, width and so on and the walking behavior such as joint angle, stride length and so on are taken as the explanatory variables. The models which identifies pedestrians from the explanatory variables are defined by the traditional neural network (NN) and Support Vector Machine (SVM). In the numerical experiments, the pedestrian's body sizes and walking behavior pictures are taken from fifteen examinees. The pedestrian's walking direction is specified as 0°, 90°, 180° and 225° and then, the accuracy was compared. The results show that the identification accuracy is the best in case of 180°-walking direction and that the accuracy of the support vector machine is better than that of the neural network.
行人行为识别个人身份
运动传感器系统的最新进展使得从传感器上观察到的人的行为可以进行个人识别。Kinect是微软为Xbox 360和Xbox One开发的动作感应输入设备。使用微软Kinect传感器(简称Kinect)的个人识别在本研究中被提出。使用Kinect可以估计行人的体型和行走行为。以身高、宽度等人体尺寸和关节角度、步幅等行走行为作为解释变量。从解释变量中识别行人的模型由传统的神经网络(NN)和支持向量机(SVM)定义。在数值实验中,采集了15名考生的身体尺寸和行走行为照片。将行人的行走方向设定为0°、90°、180°和225°,并对其精度进行比较。结果表明,在180°行走方向下的识别精度最好,支持向量机的识别精度优于神经网络的识别精度。
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