Story based representation for broadcasted sports video and automatic story segmentation,”in

This paper presents a model to represent a broadcasted sports video in a semantical way and proposes a method to segment the sports video into the semantical units for the representation. Representation of a video should clar-ify its semantical content as accurately as possible. Our model structurizes the video and gives the suitable semanti-cal descriptions to its particular time locations based on the structures of the sports video. We consider the speech tran-script as the useful information stream for the generation of the semantical descriptions. The proposed method tries to segment the speech transcript into the units of the struc-turization in a probabilistic framework based on Bayesian networks. Moreover, the association with the image stream enables us to find the corresponding video segments. In this paper, we discuss some experimental results. 1