Personal Identification Through Pedestrians’ Behavior

Xuanang Feng, Hiroki Shimokubo and Eisuke Kita ()
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Xuanang Feng: Nagoya University
Hiroki Shimokubo: Nagoya University
Eisuke Kita: Nagoya University

The Review of Socionetwork Strategies, 2018, vol. 12, issue 2, 237-252

Abstract: Abstract This article focuses on a new approach for personal identification by exploring the features of pedestrian behavior. The recent progress of a motion capture sensor system enables personal identification using human behavioral data observed from the sensor. Kinect is a motion sensing input device developed by Microsoft for Xbox 360 and Xbox One. Personal identification using the Microsoft Kinect sensor (hereafter referred to as Kinect) is presented in this study. Kinect is used to estimate body sizes and the walking behaviors of pedestrians. Body sizes such as height and width, and walking behavior such as joint angles and stride lengths, for example, are used as explanatory variables for personal identification. An algorithm for the personal identification of pedestrians is defined by a traditional neural network and by a support vector machine. In the numerical experiments, pictures of body sizes and the walking behaviors are captured from fifteen examinees through Kinect. The walking direction of pedestrians was specified as 0°, 90°, 180°, and 225°, and then the accuracies were compared. The results indicate that identification accuracy was best when the walking direction was 180°. In addition, the accuracy of the vector machine was better than that of the neural network.

Keywords: Personal identification; Pedestrian; Kinect; Neural network; Support vector machine (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s12626-018-0026-5

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