On the surplus value of semantic video analysis beyond the key frame

Typical semantic video analysis methods aim for classification of camera shots based on extracted features from a single key frame only. In this paper, we sketch a video analysis scenario and evaluate the benefit of analysis beyond the key frame for semantic concept detection performance. We developed detectors for a lexicon of 26 concepts, and evaluated their performance on 120 hours of video data. Results show that, on average, detection performance can increase with almost 40% when the analysis method takes more visual content into account.

• Type: Conference
• Year: 2005
• Where: ICMCS
• Authors: Cees G. M. Snoek, Marcel Worring, Jan-Mark Geusebroek, Dennis Koelma, Frank J. Seinstra
• Keywords: ICMCS 2005, Key Frame, Semantic Video Analysis, Video Analysis