Abstract
The automatic detection of semantic events in userspsila image and video collections is an important technique for content management and retrieval. In this paper we propose a novel semantic event detection approach by considering an event-level bag-of-features (BOF) representation to model typical events. Based on this BOF representation, semantic events are detected in a concept space instead of the original low-level visual feature space. There are two advantages of our approach: we can avoid the sensitivity problem by decreasing the influence of difficult or erroneous images or videos in measuring the event-level similarity; also we can utilize the power of higher-level concept scores in describing semantic events. Experiments over a large real consumer database confirm the effectiveness of our approach.
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