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Proceedings Paper

Passenger flow statistics across the field of view based on the depth map of the double Xtion sensors
Author(s): Zhang-qin Yin; Guo-hua Gu; Xiao-feng Bai; Tie-kun Zhao; Hai-xin Chen
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Paper Abstract

It introduces a new method to achieve the passenger flow statistics in stereo vision according to the original depth image output by the monocular Xtion sensor, aiming at the problem of algorithm with large amounts of data and realization of single field with dual camera on the basis of stereo vision. Double Xtion sensors are used to expand the range of view angle because of the monocular Xtion sensor’s limitations, whose view range is 45°*58° with small transverse view range and can’t meet the passenger flow statistics. Due to the characteristics of constant physical space dimensions, use the improved SIFT (Scale Invariant Features Transform) feature algorithm to realize the auto - stereoscopic splice of binocular original depth images. Firstly, the feature points of the reference image (the image to be matched) and the subsequent image (the image to be matched with the reference image) are obtained by SIFT algorithm, getting the location, scale and direction of the feature points and the feature points are described by means of the 128-dimensional vector .Secondly, complete the match of the feature points of the two images to calculate overlapping area, using the nearest neighbor method. Finally, image stitching is completed based on multi-resolution wavelet transform, which contains three-dimensional spatial information of the human body, thus use a method to analysis comprehensively the depth image for field detection and tracking based on the features such as the head shape, the head area the spatial position relation of the human head and shoulder and so on. The experimental results show that this method not only improve the detection accuracy and efficiency, reduce the amount of operation data, so that the system is simple in structure, but also solve many problems of passenger flow statistics based on video stream in the system, accuracy up to 93%, having high and practical application value.

Paper Details

Date Published: 21 August 2013
PDF: 7 pages
Proc. SPIE 8908, International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Sensors and Applications, 89080X (21 August 2013); doi: 10.1117/12.2032897
Show Author Affiliations
Zhang-qin Yin, Nanjing Univ. of Science and Technology (China)
Guo-hua Gu, Nanjing Univ. of Science and Technology (China)
Xiao-feng Bai, Science and Technology on Low-Light-Level Night Vision Lab. (China)
Tie-kun Zhao, Xi'an Sicong Chuangwei Opto-Electronic Co., Ltd. (China)
Hai-xin Chen, Nanjing Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 8908:
International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Sensors and Applications
Jun Ohta; Nanjian Wu; Binqiao Li, Editor(s)

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