Detecting complex events in user-generated video using concept classifiers

Guo, J., Scott, D., Hopfgartner, F. and Gurrin, C. (2012) Detecting complex events in user-generated video using concept classifiers. In: 10th International Workshop on Content-Based Multimedia Indexing (CBMI), Annecy, France, 27-29 Jun 2012, pp. 1-6. (doi: 10.1109/CBMI.2012.6269799)

Abstract

Automatic detection of complex events in user-generated videos (UGV) is a challenging task due to its new characteristics differing from broadcast video. In this work, we firstly summarize the new characteristics of UGV, and then explore how to utilize concept classifiers to recognize complex events in UGV content. The method starts from manually selecting a variety of relevant concepts, followed by constructing classifiers for these concepts. Finally, complex event detectors are learned by using the concatenated probabilistic scores of these concept classifiers as features. Further, we also compare three different fusion operations of probabilistic scores, namely Maximum, Average and Minimum fusion. Experimental results suggest that our method provides promising results. It also shows that Maximum fusion tends to give better performance for most complex events.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Hopfgartner, Dr Frank
• Authors: Guo, J., Scott, D., Hopfgartner, F., and Gurrin, C.
• College/School: College of Arts & Humanities > School of Humanities > Information Studies
• Publisher: Springer Verlag
• ISSN: 1949-3983