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Camera-based system for drafting detection while cycling

(2020) SENSORS. 20(5).
Author
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Abstract
Drafting involves cycling so close behind another person that wind resistance is significantly reduced, which is illegal during most long distance and several short distance triathlon and duathlon events. In this paper, a proof of concept for a drafting detection system based on computer vision is proposed. After detecting and tracking a bicycle through the various scenes, the distance to this object is estimated through computational geometry. The probability of drafting is then determined through statistical analysis of subsequent measurements over an extended period of time. These algorithms are tested using a static recording and a recording that simulates a race situation with ground truth distances obtained from a Light Detection And Ranging (LiDAR) system. The most accurate developed distance estimation method yields an average error of 0 . 46 m in our test scenario. When sampling the distances at periods of 1 or 2 s, simulations demonstrate that a drafting violation is detected quickly for cyclists riding at 2 m or more below the limit, while generally avoiding false positives during the race-like test set-up and five hour race simulations.
Keywords
computer vision, triathlon, cycling, object detection, object tracking, distance determination, probability theory, TRACKING

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Citation

Please use this url to cite or link to this publication:

MLA
Allebosch, Gianni, et al. “Camera-Based System for Drafting Detection While Cycling.” SENSORS, vol. 20, no. 5, 2020, doi:10.3390/s20051241.
APA
Allebosch, G., Van den Bossche, S., Veelaert, P., & Philips, W. (2020). Camera-based system for drafting detection while cycling. SENSORS, 20(5). https://doi.org/10.3390/s20051241
Chicago author-date
Allebosch, Gianni, Simon Van den Bossche, Peter Veelaert, and Wilfried Philips. 2020. “Camera-Based System for Drafting Detection While Cycling.” SENSORS 20 (5). https://doi.org/10.3390/s20051241.
Chicago author-date (all authors)
Allebosch, Gianni, Simon Van den Bossche, Peter Veelaert, and Wilfried Philips. 2020. “Camera-Based System for Drafting Detection While Cycling.” SENSORS 20 (5). doi:10.3390/s20051241.
Vancouver
1.
Allebosch G, Van den Bossche S, Veelaert P, Philips W. Camera-based system for drafting detection while cycling. SENSORS. 2020;20(5).
IEEE
[1]
G. Allebosch, S. Van den Bossche, P. Veelaert, and W. Philips, “Camera-based system for drafting detection while cycling,” SENSORS, vol. 20, no. 5, 2020.
@article{8650005,
  abstract     = {Drafting involves cycling so close behind another person that wind resistance is significantly reduced, which is illegal during most long distance and several short distance triathlon and duathlon events. In this paper, a proof of concept for a drafting detection system based on computer vision is proposed. After detecting and tracking a bicycle through the various scenes, the distance to this object is estimated through computational geometry. The probability of drafting is then determined through statistical analysis of subsequent measurements over an extended period of time. These algorithms are tested using a static recording and a recording that simulates a race situation with ground truth distances obtained from a Light Detection And Ranging (LiDAR) system. The most accurate developed distance estimation method yields an average error of     0 . 46     m in our test scenario. When sampling the distances at periods of 1 or 2 s, simulations demonstrate that a drafting violation is detected quickly for cyclists riding at 2 m or more below the limit, while generally avoiding false positives during the race-like test set-up and five hour race simulations.},
  articleno    = {1241},
  author       = {Allebosch, Gianni and Van den Bossche, Simon and Veelaert, Peter and Philips, Wilfried},
  issn         = {1424-8220},
  journal      = {SENSORS},
  keywords     = {computer vision,triathlon,cycling,object detection,object tracking,distance determination,probability theory,TRACKING},
  language     = {eng},
  number       = {5},
  pages        = {24},
  title        = {Camera-based system for drafting detection while cycling},
  url          = {http://dx.doi.org/10.3390/s20051241},
  volume       = {20},
  year         = {2020},
}

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