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2008
Springer

Detecting and Clustering Multiple Takes of One Scene

9 years 4 months ago
Detecting and Clustering Multiple Takes of One Scene
Abstract. In applications such as video post-production users are confronted with large amounts of redundant unedited raw material, called rushes. Viewing and organizing this material are crucial but time consuming tasks. Typically multiple but slightly different takes of the same scene can be found in the rushes video. We propose a method for detecting and clustering takes of one scene shot from the same or very similar camera positions. It uses a variant of the LCSS algorithm to find matching subsequences in sequences of visual features extracted from the source video. Hierarchical clustering is used to group the takes of one scene. The approach is evaluated in terms of correctly assigned takes using manually annotated ground truth.
Werner Bailer, Felix Lee, Georg Thallinger
Added 31 May 2010
Updated 31 May 2010
Type Conference
Year 2008
Where MMM
Authors Werner Bailer, Felix Lee, Georg Thallinger
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