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Keyframe Extraction for Video Tagging and Summarization

Damian Borth; Adrian Ulges; Christian Schulze; Thomas Breuel
In: Gesellschaft für Informatik (Hrsg.). Informatiktage 2008. GI-Informatiktage (Informatik), Fachwissenschaftlicher Informatik-Kongress, March 14-15, Bonn, Germany, Pages 45-48, LNI, Vol. S-6, GI, 3/2008.


Currently, online video distributed via online video platforms like YouTube experiences more and more popularity. We propose an approach of keyframe extraction based on unsupervised learning for video retrieval and video summarization. Our approach uses shot boundary detection to segment the video into shots and the k-means algorithm to determine cluster representatives for each shot that are used as keyframes. Furthermore we performed an additional clustering on the extracted keyframes to provide a video summarization. To test our methods we used a database of videos downloaded from YouTube where our results show (1) an improvement of retrieval and (2) compact summarization examples.