Abstract
An application for content-based annotation and retrieval of videos can be found in the sport domain, where videos are annotated in order to produce short summaries for news and sports programmes, edited reusing the video clips that show important highlights and the players involved in them. The problem of detecting and recognizing faces in broadcast videos is a widely studied topic. However, in the case of sports videos in general, and soccer videos in particular, the current techniques are not suitable for the task of face detection and recognition, due to the high variations in pose, illumination, scale and occlusion that may happen in an uncontrolled environment.
In this paper we present a method for face detection and recognition, with associated metric, that copes with these problems. The face detection algorithm adds a filtering stage to the Viola and Jones Adaboost detector, while the recognition algorithm exploits i) local features to describe a face, without requiring a precise localization of the distinguishing parts of a face, and ii) the set of poses to describe a person and perform a more robust recognition.
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Ballan, L., Bertini, M., Del Bimbo, A., Nunziati, W. (2007). Automatic Detection and Recognition of Players in Soccer Videos. In: Qiu, G., Leung, C., Xue, X., Laurini, R. (eds) Advances in Visual Information Systems. VISUAL 2007. Lecture Notes in Computer Science, vol 4781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76414-4_11
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DOI: https://doi.org/10.1007/978-3-540-76414-4_11
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