Soccer line mark segmentation with stochastic watershed transform
- URL: http://arxiv.org/abs/2108.06432v1
- Date: Sat, 14 Aug 2021 00:51:12 GMT
- Title: Soccer line mark segmentation with stochastic watershed transform
- Authors: Daniel Berj\'on, Carlos Cuevas, Narciso Garc\'ia
- Abstract summary: We propose a novel strategy to automatically and accurately segment line markings based on a watershed transform.
The strategy has been tested on a new and public database composed by 60 annotated images from matches in five stadiums.
- Score: 1.7188280334580195
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Augmented reality applications are beginning to change the way sports are
broadcast, providing richer experiences and valuable insights to fans. The
first step of augmented reality systems is camera calibration, possibly based
on detecting the line markings of the field of play. Most existing proposals
for line detection rely on edge detection and Hough transform, but optical
distortion and extraneous edges cause inaccurate or spurious detections of line
markings. We propose a novel strategy to automatically and accurately segment
line markings based on a stochastic watershed transform that is robust to
optical distortions, since it makes no assumptions about line straightness, and
is unaffected by the presence of players or the ball in the field of play.
Firstly, the playing field as a whole is segmented completely eliminating the
stands and perimeter boards. Then the line markings are extracted.
The strategy has been tested on a new and public database composed by 60
annotated images from matches in five stadiums. The results obtained have
proven that the proposed segmentation algorithm allows successful and precise
detection of most line mark pixels.
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