Unsupervised high-quality soccer field segmentation

Field segmentation is a fundamental step in many soccer applications. However, despite its importance, the existing segmentation algorithms are not able to provide successful results in complex scenarios. Moreover, they require the manual selection of several parameters, hindering their usability. Here, an unsupervised field segmentation strategy based on the estimation of the probability density function of the green chromacity of the image is proposed. Results show its ability to provide high-quality results in a wide variety of scenarios.