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Accurate ball detection in soccer images using probabilistic analysis of salient regions

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Abstract

Automatic sport video analysis has became one of the most attractive research fields in the areas of computer vision and multimedia technologies. In particular, there has been a boom in soccer video analysis research. This paper presents a new multi-step algorithm to automatically detect the soccer ball in image sequences acquired from static cameras. In each image, candidate ball regions are selected by analyzing edge circularity and then ball patterns are extracted representing locally affine invariant regions around distinctive points which have been highlighted automatically. The effectiveness of the proposed methodologies is demonstrated through a huge number of experiments using real balls under challenging conditions, as well as a favorable comparison with some of the leading approaches from the literature.

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Acknowledgments

The authors are grateful to Jasna Maver for advice and suggestions. The authors thank Liborio Capozzo and Arturo Argentieri for technical support in the setup of the devices used for data acquisition.

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Authors and Affiliations

  1. Institute of Optics, National Research Council of Italy, via della Libertà 3, 73010 , Arnesano, Lecce, Italy

    Marco Leo

  2. Institute of Intelligent Systems for Automation, National Research Council of Italy, via Amendola 122, 70126 , Bari, Italy

    Pier Luigi Mazzeo, Massimiliano Nitti & Paolo Spagnolo

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  1. Marco Leo
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  2. Pier Luigi Mazzeo
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  3. Massimiliano Nitti
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  4. Paolo Spagnolo
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Correspondence to Marco Leo.

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Leo, M., Mazzeo, P.L., Nitti, M. et al. Accurate ball detection in soccer images using probabilistic analysis of salient regions. Machine Vision and Applications 24, 1561–1574 (2013). https://doi.org/10.1007/s00138-013-0518-9

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  • DOI: https://doi.org/10.1007/s00138-013-0518-9

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