Computing at Glasgow University
Paper ID: 8948

Video Redundancy Detection in Rushes Collection
Reede,R.e.n. Punitha,P. Jose,J.M.

Publication Type: Conference Proceedings
Appeared in: ACM MM workshop on Video Summarization
Page Numbers :
Publisher: N/A
Year: 2008

The rushes is a collection of raw material videos. There are various redundancies, such as rainbow screen, clipboard shot, white/black view, and unnecessary re-take. This pa- per develops a set of solutions to remove these video redun- dancies as well as an e®ective system for video summarisa- tion. We regard manual editing e®ects, e.g. clipboard shots, as di®erentiators in the visual language. A rushes video is therefore divided into a group of subsequences, each of which stands for a re-take instance. A graph matching algorithm is proposed to estimate the similarity between re-takes and suggests the best instance for content presentation. The ex- periments on the Rushes 2008 collection show that a video can be shortened to 4%-16% of the original size by redun- dancy detection. This signi¯cantly reduces the complexity in content selection and leads to an e®ective and e±cient video summarisation system.

Keywords: video summarisation

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