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In this paper, we propose a fast and accurate video retrieval algorithm using random projections, an indexing structure and parallel computing. The video sequences are represented by low dimensional temporal trajectories in a set of low dimensional spaces through scaling and random projections. A kd-tree structure is used for efficient data access. We also develop an efficient retrieval algorithm...
With the phenomenal growth of the online and personal video repositories, an efficient and robust example-based video search solution is required to support applications like query by clip, query by capture, and repeated clip detection. In this letter, video sequences are represented as temporal trajectories via scaling and lower dimensional representation of the video frame luminance field, and a...
Efficient indexing is a key in content-based video retrieval solutions. In this paper we propose a new dynamic indexing scheme based on the kd-tree structure. Video sequences are first represented as traces in an appropriate low dimensional space via luminance field scaling and PCA projection. Then, the indexing scheme is applied to give the video database a manageable structure. Being able to handle...
Efficient indexing and robust retrieval are key features for an effective video retrieval system. In this paper we represent video sequences as traces in an appropriate low dimensional space via luminance field scaling and PCA projection, and introduce a combination of top-down and bottom-up strategies for indexing. Various means of introducing distortions in query clips are considered and several...
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