Evidence map›Paper›PMID 36702910›Full record

ArticleScientific reports2023

A fully automatic method for segmentation of soccer playing fields.

Carlos Cuevas, Daniel Berjón, Narciso García

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Carlos Cuevas *Grupo de Tratamiento de Imágenes (GTI), Information Processing and Telecommunications Center (IPTC), Universidad Politécnica de Madrid (UPM), 28040, Madrid, Spain. carlos.cuevas@upm.es.
Daniel Berjón *Grupo de Tratamiento de Imágenes (GTI), Information Processing and Telecommunications Center (IPTC), Universidad Politécnica de Madrid (UPM), 28040, Madrid, Spain.
Narciso García *Grupo de Tratamiento de Imágenes (GTI), Information Processing and Telecommunications Center (IPTC), Universidad Politécnica de Madrid (UPM), 28040, Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper proposes a strategy to segment the playing field in soccer images, suitable for integration in many soccer image analysis applications. The combination of a green chromaticity-based analysis and an analysis of the chromatic distortion using full-color information, both at the pixel-level, allows segmenting the green areas of the images. Then, a fully automatic post-processing block at the region-level discards the green areas that do not belong to the playing field. The strategy has been evaluated with hundreds of annotated images from matches in several stadiums with different grass shades and light conditions. The results obtained have been of great quality in all the images, even in those with the most complex lighting conditions (e.g., high contrast between sunlit and shadowed areas). In addition, these results have improved those obtained with leading state-of-the-art playing field segmentation strategies.

Identifiers

PMID36702910
PMCPMC9879963

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.