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Author Gkalelis, Nikolaos ♦ Mezaris, Vasileios ♦ Kompatsiaris, Ioannis
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Description in Proc. 9th International Workshop on Content-Based Multimedia Indexing (CBMI 2011
In this paper a new approach to video event detection is presented, combining visual concept detection scores with a new dimensionality reduction technique. Specifically, a video is first decomposed to a sequence of shots, and trained visual concept detectors are used to represent video content with model vector sequences. Subsequently, an improved subclass discriminant analysis method is used to derive a concept subspace for detecting and recognizing high-level events. In this space, the median Hausdorff distance is used to implicitly align and compare event videos of different lengths, and the nearest neighbor rule is used for recog-nizing the event depicted in the video. Evaluation results obtained by our participation in the Multimedia Event De-tection Task of the TRECVID 2010 competition verify the effectiveness of the proposed approach for event detection and recognition in large scale video collections. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2011-01-01