Publikation
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.
Zusammenfassung
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.