Multi-target detection and positioning in crowds using multiple camera surveillance

Jiahu Huang; Qiuyu Zhu; Yufeng Xing

doi:10.1117/12.2302960

10 April 2018 Multi-target detection and positioning in crowds using multiple camera surveillance

Jiahu Huang, Qiuyu Zhu, Yufeng Xing

Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 106150C (2018) https://doi.org/10.1117/12.2302960
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China

Abstract

In this study, we propose a pixel correspondence algorithm for positioning in crowds based on constraints on the distance between lines of sight, grayscale differences, and height in a world coordinates system. First, a Gaussian mixture model is used to obtain the background and foreground from multi-camera videos. Second, the hair and skin regions are extracted as regions of interest. Finally, the correspondences between each pixel in the region of interest are found under multiple constraints and the targets are positioned by pixel clustering. The algorithm can provide appropriate redundancy information for each target, which decreases the risk of losing targets due to a large viewing angle and wide baseline. To address the correspondence problem for multiple pixels, we construct a pixel-based correspondence model based on a similar permutation matrix, which converts the correspondence problem into a linear programming problem where a similar permutation matrix is found by minimizing an objective function. The correct pixel correspondences can be obtained by determining the optimal solution of this linear programming problem and the three-dimensional position of the targets can also be obtained by pixel clustering. Finally, we verified the algorithm with multiple cameras in experiments, which showed that the algorithm has high accuracy and robustness.

Citation Download Citation

Jiahu Huang, Qiuyu Zhu, and Yufeng Xing "Multi-target detection and positioning in crowds using multiple camera surveillance", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106150C (10 April 2018); https://doi.org/10.1117/12.2302960

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