# A Monocular Vision System for Playing Soccer in Low Color Information Environments

arXiv: https://arxiv.org/abs/1809.11078 · HTML: https://mlsanity.com/paper/1809.11078/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Sep 2018.

## Built on by (most cited first, 2 of 2)

- [Position and Altitude of the Nao Camera Head from Two Points on the Soccer Field plus the Gravitational Direction](https://mlsanity.com/paper/2407.03041/) (2024)
- [Efficient Lines Detection for Robot Soccer](https://mlsanity.com/paper/2507.19469/) (2025)

## Abstract (arXiv)

Humanoid soccer robots perceive their environment exclusively through cameras. This paper presents a monocular vision system that was originally developed for use in the RoboCup Humanoid League, but is expected to be transferable to other soccer leagues. Recent changes in the Humanoid League rules resulted in a soccer environment with less color coding than in previous years, which makes perception of the game situation more challenging. The proposed vision system addresses these challenges by using brightness and texture for the detection of the required field features and objects. Our system is robust to changes in lighting conditions, and is designed for real-time use on a humanoid soccer robot. This paper describes the main components of the detection algorithms in use, and presents experimental results from the soccer field, using ROS and the igus Humanoid Open Platform as a testbed. The proposed vision system was used successfully at RoboCup 2015.