YouTubeEvent: On large-scale video event classification

Bingbing Ni, Yang Song, Ming Zhao
2011 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)  
In this work, we investigate the problem of general event classification from uncontrolled YouTube videos. It is a challenging task due to the number of possible categories and large intra-class variations. On one hand, how to define proper event category labels and how to obtain training samples for these categories need to be explored; on the other hand, it is non-trivial to achieve satisfactory classification performance. To address these problems, a text mining pipeline is first proposed to
more » ... automatically discover a collection of video event categories. Part-of-Speech (POS) analysis is applied to YouTube video titles and descriptions, and WordNet hierarchy is employed to refine the category selection. This results in 29, 163 video event categories. A POS-based query method is then applied to video titles, and 6, 538, 319 video samples are obtained from YouTube to represent these categories. To improve classification performance, video content-based features are complemented with scores from a set of classifiers, which can be regarded as a type of high-level features. Extensive evaluations demonstrate the effectiveness of the proposed automatic event label mining technique, and our feature fusion scheme shows encouraging classification results.
doi:10.1109/iccvw.2011.6130430 dblp:conf/iccvw/NiSZ11 fatcat:763dv7dbjffbdg5iydhofnyd6e