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Automatic 3D Video Summarization: Key Frame Extraction from Self-Similarity

Huang, P, Hilton, A and Starck, J (2008) Automatic 3D Video Summarization: Key Frame Extraction from Self-Similarity In: Fourth International Symposium on 3D Data Processing, Visualization and Transmission, 2008-06-18 - 2008-06-20, Georgia Institute of Technology, Atlanta, GA, USA.

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In this paper we present an automatic key frame selection method to summarise 3D video sequences. Key-frame selection is based on optimisation for the set of frames which give the best representation of the sequence according to a rate-distortion trade-off. Distortion of the summarization from the original sequence is based on measurement of self-similarity using volume histograms. The method evaluates the globally optimal set of key-frames to represent the entire sequence without requiring pre-segmentation of the sequence into shots or temporal correspondence. Results demonstrate that for 3D video sequences of people wearing a variety of clothing the summarization automatically selects a set of key-frames which represent the dynamics. Comparative evaluation of rate-distortion characteristics with previous 3D video summarization demonstrates improved performance.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Communication Systems Research
Authors :
Huang, P
Hilton, A
Starck, J
Date : 2008
Depositing User : Symplectic Elements
Date Deposited : 31 Jan 2012 14:30
Last Modified : 31 Oct 2017 14:15

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