Real-time passenger counting in buses using dense stereovision
Open accessAbstract
We are interested particularly in the estimation of passenger flows entering or exiting from buses. To achieve this measurement, we propose a counting system based on stereo vision. To extract three-dimensional information in a reliable way, we use a dense stereo-matching procedure in which the winner-takes-all technique minimizes a correlation score. This score is an improved version of the sum of absolute differences, including several similarity criteria determined on pixels or regions to be matched. After calculating disparity maps for each image, morphological operations and a binarization with multiple thresholds are used to localize the heads of people passing under the sensor. The markers describing the heads of the passengers getting on or off the bus are then tracked during the image sequence to reconstitute their trajectories. Finally, people are counted from these reconstituted trajectories. The technique suggested was validated by several realistic experiments. We showed that it is possible to obtain counting accuracy of 99% and 97% on two large realistic data sets of image sequences showing realistic scenarios.
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Real-time passenger counting using dense stereovision tracks heads and is effective in crowded situations, but requires many cameras and can be inaccurate with hats.
“This approach proved to be effective in crowded situations, but it requires having many cameras installed to cover the whole space for passengers and can produce inaccurate results in cases where passengers wear hats, etc.”
From A Review of Passenger Counting in Public Transport Concepts with Solution Proposal Based on Image Processing and Machine Learning (2024) · cites this paper as [25]
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- Authors
- Yahiaoui, T., Khoudour, L., & Meurie, C.
- Affiliations
- Institut National de Recherche sur les Transports et Leur Sècurité
- Université de technologie de belfort-montbéliard (FR)
- Corresponding author
- Yahiaoui, Tarek
- Venue
- Journal of Electronic Imaging
- Publisher
- SPIE-Intl Soc Optical Eng
- Published
- 2010-07-01
- Volume
- 19
- Issue
- 3
- Pages
- 1-11
- ISSN
- 1017-9909 (ISSN-L)
- 1560-229X
- OpenAlex
- W2099942418
- Cited by
- 37
- References
- 32
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 3 · 2023: 2 · 2022: 1 · 2021: 6 · 2019: 2 · 2018: 4 · 2017: 1 · 2016: 2 · 2015: 1 · 2014: 2 · 2013: 4 · 2012: 3
- FWCI
- 2.97
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Electronic Imaging (publishedVersion)
- HAL (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Keywords
- dense stereo matching, sum of absolute differences, disparity map, head detection, human tracking, trajectory reconstruction, morphological operations, public transport monitoring
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