This paper proposes a scheme to detect and locate the players and the ball on the grass playfield in soccer videos. We put forward a shape analysisbased approach to identify the players and the ball from the roughly extracted foreground, which is obtained by a trained, color histogram-based playfield detector and connected component analysis. We employ Euclidean distance transform to extract skeletons for every foreground blob, and then perform shape analysis to remove false alarms (non-player and non-ball blobs) and cut-off the artifacts (mostly due to playfield lines) based on skeleton pruning and reverse Euclidean distance transform. Results are given to demonstrate the proposed algorithm works well in soccer video clips. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Huang, Y., Llach, J., & Bhagavathy, S. (2007). Players and ball detection in soccer videos based on color segmentation and shape analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4577 LNCS, pp. 416–425). Springer Verlag. https://doi.org/10.1007/978-3-540-73417-8_50
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