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.

Automatic detection and recognition of players in soccer videos / Lamberto Ballan; Marco Bertini; Alberto Del Bimbo; Walter Nunziati. - STAMPA. - 4781:(2007), pp. 105-116. (Intervento presentato al convegno International Conference on Visual Information Systems (VISUAL) tenutosi a Shanghai, China nel June 28-29).

Automatic detection and recognition of players in soccer videos

BALLAN, LAMBERTO;BERTINI, MARCO;DEL BIMBO, ALBERTO;NUNZIATI, WALTER
2007

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.
2007
Proc. of International Conference on Visual Information Systems (VISUAL)
International Conference on Visual Information Systems (VISUAL)
Shanghai, China
June 28-29
Lamberto Ballan; Marco Bertini; Alberto Del Bimbo; Walter Nunziati
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/348241
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