Automatic semantic annotation of video streams allows to extract significant clips for archiving and retrieval of video content. In this paper, we present a system that performs automatic annotation of soccer videos, detecting principal highlights, and recognizing identity of players. Highlight detection is carried out by means of finite state machines that encode domain knowledge, while player identification is based on face detection, and on the analysis of contextual information such as jersey's numbers and superimposed text captions. Results obtained on actual soccer videos shows overall highlight detection rates of about 90%. Lower, but still promising, accuracy is achieved on the very difficult player identification task. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Bertini, M., Del Bimbo, A., & Nunziati, W. (2005). Automatic annotation of sport video content. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3773 LNCS, pp. 1066–1078). https://doi.org/10.1007/11578079_109
Mendeley helps you to discover research relevant for your work.