The automatic detection of semantic events in users’ 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 eventlevel 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 lowlevel 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.
Wei Jiang, Alexander C. Loui