On clustering and retrieval of video shots through temporal slices analysis

Based on the analysis of temporal slices, we propose novel approaches for clustering and retrieval of video shots. Temporal slices are a set of two-dimensional (2-D) images extracted along the time dimension of an image volume. They encode rich set of visual patterns for similarity measure. In this...

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Bibliographic Details
Main Authors: NGO, Chong-wah, PONG, Ting-Chuen, ZHANG, Hong-Jiang
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2002
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Online Access:https://ink.library.smu.edu.sg/sis_research/6335
https://ink.library.smu.edu.sg/context/sis_research/article/7338/viewcontent/itm02.pdf
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Institution: Singapore Management University
Language: English
Description
Summary:Based on the analysis of temporal slices, we propose novel approaches for clustering and retrieval of video shots. Temporal slices are a set of two-dimensional (2-D) images extracted along the time dimension of an image volume. They encode rich set of visual patterns for similarity measure. In this paper, we first demonstrate that tensor histogram features extracted from temporal slices are suitable for motion retrieval. Subsequently, we integrate both tensor and color histograms for constructing a two-level hierarchical clustering structure. Each cluster in the top level contains shots with similar color while each cluster in bottom level consists of shots with similar motion. The constructed structure is then used for the cluster-based retrieval. The proposed approaches are found to be useful particularly for sports games, where motion and color are important visual cues when searching and browsing the desired video shots.