Abstract—In this paper, we propose a video summarization
system for analyzing basketball game videos. In contrast to
previous video analysis technologies employing only visual and
motion features to do video filtering, we add audio features to do
video summarization in the system. First, we extract replay
highlights by special effect detection. Next, we filter landscape
shots using color range pixel and fast motion activity. Then, the
corresponding audio features extracted from these landscape
shots are used to identify landscape shot highlights by an SVM.
Finally, we integrate the replay highlights and landscape shot
highlights to complete the video summarization. From the
experimental results, we find that the accuracy on the special
effect detection, landscape shot extraction, and landscape shot
highlight detection is very high. Thus, the final video
summarization has high recall values on highlight extraction.
Index Terms—Basketball video, landscape shot highlight, replay highlight, video summarization.
Yin-Fu Huang is with National Yunlin University of Science and Technology, Yunlin, Taiwan 640 (e-mail: firstname.lastname@example.org).
Wei-Chung Chen is with Chung Shan Institute of Science and Technology, Taoyuan, Taiwan 325 (e-mail: email@example.com).
Cite: Yin-Fu Huang and Wei-Chung Chen, "Rushes Video Summarization by Audio-Filtering Visual Features," International Journal of Machine Learning and Computing vol.4, no. 4, pp. 359-364, 2014.