The exploitation of semantic information in videos is difficult because of the large difference in representations, levels of knowledge and abstract episodes. Traditional image/video understanding and indexing is formulated in terms of low-level features describing image/video structure and intensity, while high-level knowledge such as common sense and human perceptual knowledge are encoded. This paper attempts to bridge this gap through the integration of image/video analysis algorithms with multi-level semantic network to interpret the baseball video.
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