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SVM-based Video Segmentation and Annotation of Lectures and Conferences
english
2014
Proceedings of the 9th International Conference on Computer Vision Theory and Applications
english
This paper presents a classification system for video lectures and conferences based on Support Vector Machines (SVM). The aim is to classify videos into four different classes (talk, presentation, blackboard, mix). On top of this, the system further analyses presentation segments to detect slide transitions, animations and dynamic content such as video inside the presentation. The developed approach uses various colour and facial features from two different datasets of several hundred hours of
doi:10.5220/0004686004250432
dblp:conf/visapp/MasneriS14
fatcat:dqjiu2y6jfcwnc6hf7bii4n75e