Abstract
Laser devices have received increasing attention in numerous computer-aided applications such as automatic control, 3D modeling and virtual reality. In this paper, aiming at people counting, we propose a novel people detection and tracking method based on the multipoint infrared laser, which can further facilitate intelligent scene modeling and analysis. In our method, a camera with the infrared lens filter is utilized to capture the monitored scene where an array of infrared spots is produced by the multipoint infrared laser. We build a spatial background model based on locations of spots. Pedestrians are detected by clustering of foreground spots. Then, our method tracks and counts the detected pedestrians via inferring the forward–backward motion consistency. Both quantitative and qualitative evaluation and comparison are conducted, and the experimental results demonstrate that the proposed method achieves excellent performance in challenging scenarios.
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Acknowledgements
The authors would like to thank Weina Jiang and Hengzheng Zhu who partly joined this work when they were postgraduate students at Sun Yat-sen University, and thank the editors and reviewers for their valuable suggestions on improving the quality of the paper.
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This work was supported by the National Natural Science Foundation of China (61402120, 61472455, 61379112), the Natural Science Foundation of Guangdong Province (2014A030310348 and 2014A030313154), and Guangdong Provincial Department of Science and Technology (GDST16EG04) 2016A050503024.
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Wu, H., Gao, C., Cui, Y. et al. Multipoint infrared laser-based detection and tracking for people counting. Neural Comput & Applic 29, 1405–1416 (2018). https://doi.org/10.1007/s00521-017-3196-0
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DOI: https://doi.org/10.1007/s00521-017-3196-0