用二維C型樹做視訊資料索引與相似擷取

Abstract

Video data contains a large amount of spatial and temporal information.A video information system must be provided to manage a variety ofinformation in video data, including stoing video data, maintainingvideo indices, processing video query and retrieving video information.Chang et. al. had proposed an effective 2D string approach for spatialindexing of image data. In this dissertation, we extend this iconicapproach and apply it to video data indexing. We investigate a new knowledgemodel, 2D C-tree, to characterize the spatial information of video content.Not only does the new representation keep the whole spatial relationshipsamong objects in an original image, but the ordered labeled tree is moresuitable for spatial reasoning and image retrieval.The indexing technique represents the spatial content within individualframes and an ordering set of 2D C- trees for a video sequence is constructed.The ordering set of 2D C-trees then becomes the representative indexing of avideo sequence. The similarity retrieval of video matching problem becomesthe problem of video sequence matching by computing the similarity, or theminimum cost of matched frames. A prototype video information system is alsodeveloped to validate the effectiveness of video data indexing and similarityretrieval based on 2D C-trees.