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S. Afanou, "People counting in railway environment using computer vision", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 1, Paper 17.4, 2022, doi:10.4203/ccc.1.17.4

Keywords: re-identification, detection, counting, tracking, computer vision, segmentation.

Abstract

Ensuring passengers' safety and comfort is a daily comfort for railway operators. In order to correctly size their transport plan, it is necessary to know in real time the number of users present in the trains. With the advent of artificial intelligence, several techniques now make it possible to detect and track passengers effectively. The combination of these 2 techniques can then make it possible to carry out a relevant count. In this article, we compare 2 counting methods based on the one hand on the detection of faces, on the other hand on the segmentation of shapes and their reidentification. We will show the promising results obtained, as well as the impact of physical phenomena such as occultation on the precision of the counting performed.

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Front Page Browse CCC CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Conferences ISSN 2753-3239 CCC: 1 PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 17.4 People counting in railway environment using computer vision S. Afanou Rolling stocks engineering center, SNCF Voyageurs Le Mans, France doi:10.4203/ccc.1.17.4 Full Bibliographic Reference for this paper S. Afanou, "People counting in railway environment using computer vision", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 1, Paper 17.4, 2022, doi:10.4203/ccc.1.17.4 Keywords: re-identification, detection, counting, tracking, computer vision, segmentation. Abstract Ensuring passengers' safety and comfort is a daily comfort for railway operators. In order to correctly size their transport plan, it is necessary to know in real time the number of users present in the trains. With the advent of artificial intelligence, several techniques now make it possible to detect and track passengers effectively. The combination of these 2 techniques can then make it possible to carry out a relevant count. In this article, we compare 2 counting methods based on the one hand on the detection of faces, on the other hand on the segmentation of shapes and their reidentification. We will show the promising results obtained, as well as the impact of physical phenomena such as occultation on the precision of the counting performed. download the full-text of this paper (PDF, 9 pages, 607 Kb) go to the previous paper go to the next paper return to the table of contents return to the volume description
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