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Camera-Based System for Drafting Detection While Cycling.

Gianni Allebosch^1,2, Simon Van den Bossche¹, Peter Veelaert^1,2

¹TELIN-IPI, Ghent University, Sint-Pietersnieuwstraat 41, B-9000 Gent, Belgium.

Sensors (Basel, Switzerland)

|February 29, 2020

Summary

This summary is machine-generated.

This study introduces a computer vision system to detect illegal drafting in cycling races. The system accurately estimates cyclist distances, enabling rapid identification of violations while minimizing false positives.

Keywords:

computer vision cycling distance determination object detection object tracking probability theory triathlon

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Area of Science:

Sports Science
Computer Vision
Computational Geometry

Background:

Drafting in cycling, riding closely behind another competitor to reduce wind resistance, is prohibited in many triathlon and duathlon events.
Existing methods for detecting drafting are limited, necessitating advanced technological solutions for fair competition.

Purpose of the Study:

To propose and validate a proof-of-concept computer vision system for automated drafting detection in cycling.
To develop algorithms for accurate bicycle tracking, distance estimation, and statistical analysis of drafting probability.

Main Methods:

Bicycle detection and tracking using computer vision techniques.
Distance estimation through computational geometry, validated against Light Detection And Ranging (LiDAR) data.
Statistical analysis of sequential distance measurements to determine drafting violations.

Main Results:

The most accurate distance estimation method achieved an average error of 0.46 meters.
Simulations showed rapid detection of drafting violations (cyclists within 2m of the limit) with 1-2 second sampling intervals.
The system demonstrated a low false positive rate in race simulations exceeding five hours.

Conclusions:

The proposed computer vision system offers a viable solution for detecting illegal drafting in cycling events.
Accurate distance estimation and statistical analysis are key to reliable drafting detection.
This technology can enhance fair play and officiating in endurance cycling competitions.