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Scene text recognition and tracking to identify athletes in sport videos

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Abstract

We present an athlete identification module forming part of a system for the personalization of sport video broadcasts. The aim of this module is the localization of athletes in the scene, their identification through the reading of names or numbers printed on their uniforms, and the labelling of frames where athletes are visible. Building upon a previously published algorithm we extract text from individual frames and read these candidates by means of an optical character recognizer (OCR). The OCR-ed text is then compared to a known list of athletes’ names (or numbers), to provide a presence score for each athlete. Text regions are tracked in subsequent frames using a template matching technique. In this way blurred or distorted text, normally unreadable by the OCR, is exploited to provide a denser labelling of the video sequences. Extensive experiments show that the method proposed is fast, robust and reliable, out-performing results of other systems in the literature.

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Acknowledgements

This work has been supported by the European Union under the Strep Project FP7 215248: My eDirector 2012. The authors would like to thank Paul Chippendale for his careful reading of the manuscript.

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  1. FBK-irst, Via Sommarive 18, 38123, Povo, Trento, Italy

    Stefano Messelodi & Carla Maria Modena

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  1. Stefano Messelodi
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  2. Carla Maria Modena
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Correspondence to Carla Maria Modena.

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Messelodi, S., Modena, C.M. Scene text recognition and tracking to identify athletes in sport videos. Multimed Tools Appl 63, 521–545 (2013). https://doi.org/10.1007/s11042-011-0878-y

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