Abstract
Conference Title: ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Conference Start Date: 2014, May 4 Conference End Date: 2014, May 9 Conference Location: Florence, Italy Recognizing video events has been a very active field of interest. The diversity of videos captured in complex environments and under difficult conditions makes the event recognition a challenging task. In this paper, we present a video event recognition method which exploits the power of graphs for representing the structural organization of the features and the success of the Bag-of-Words approach. Our method combines the Scale Invariant Feature Transform and the SpaceTime Interest Point features to characterize the video. To model the spatio-temporal relations among these features, a graph-based representation is used for each video. Then, the video is indexed based on a histogram of frequent sub-graphs. To evaluate our method, we have used the Columbia Consumer Video dataset. The experimental results show the efficiency of the proposed method. [PUBLICATION ABSTRACT]