ON THE SURPLUS VALUE OF SEMANTIC VIDEO ANALYSIS BEYOND THE KEY FRAME (WedAmOR7)

Author(s) : Cees Snoek (University of Amsterdam, Netherlands) Marcel Worring (University of Amsterdam, Netherlands) Jan-Mark Geusebroek (University of Amsterdam, Netherlands) Dennis Koelma (University of Amsterdam, Netherlands) Frank Seinstra (University of Amsterdam, Netherlands)

Abstract : 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.

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