Automatic annotation of Web videos.
Journal
Proceedings of the 2011 IEEE International Conference on Multimedia and Expo, ICME 2011, 11-15 July, 2011, Barcelona, Catalonia, Spain
Pages
1-6
Date Issued
2011
Author(s)
Sun, Shih-Wei
Wang, Yu-Chiang Frank
Hung, Yao-Ling
Chang, Chia-Ling
Chen, Kuan-Chieh
Cheng, Shih-Sian
Wang, Hsin-Min
Liao, Hong-Yuan Mark
Abstract
Most Web videos are captured in uncontrolled environments (e.g. videos captured by freely-moving cameras with low resolution); this makes automatic video annotation very difficult. To address this problem, we present a robust moving foreground object detection method followed by the integration of features collected from heterogeneous domains. We advance SIFT feature matching and present a probabilistic framework to construct consensus foreground object templates (CFOT). The CFOT can detect moving foreground objects of interest across video frames, and this allows us to extract visual features from foreground regions of interest. Together with the use of audio features, we are able to improve resulting annotation accuracy. We conduct experiments and achieve promising results on a Web video dataset collected from YouTube.
Type
conference paper