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Background subtraction in real applications: Challenges, current models and future directions
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“When integrated with ML, they can adapt to gradual changes in lighting and background shifts.”
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 [61]
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“They are suitable for fixed-point passenger counting where the camera is stationary, and background subtraction is effective in relatively stable environments like bus stops or entry gates.”
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 [61]
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Self-citation
Metadata
- Authors
- Garcia-Garcia, B., Bouwmans, T., & Rosales Silva, A. J.
- Affiliations
- Laboratoire Mathématiques, Image et Applications (FR)
- Corresponding author
- Bouwmans, Thierry
- ORCID
- Bouwmans, Thierry
- Venue
- Computer Science Review
- Publisher
- Elsevier BV
- Published
- 2020-02
- Volume
- 35
- Pages
- 100204
- ISSN
- 1574-0137 (ISSN-L)
- OpenAlex
- W2983488121
- Cited by
- 337
- References
- 534
- Citations by year
- 2026: 16 · 2025: 40 · 2024: 47 · 2023: 65 · 2022: 71 · 2021: 46 · 2020: 41
- FWCI
- 18.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Computer Science Review (acceptedVersion)
- HAL (submittedVersion, other-oa)
- Funders
- Consejo Nacional de Ciencia y Tecnología
- 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 Neural Network Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Infrared Target Detection Methodologies
- Keywords
- background subtraction, moving object detection, foreground-background separation, traffic monitoring, background modeling, omnidirectional camera, CCD detector
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