TY - GEN
T1 - Highlight ranking for broadcast tennis video based on multi-modality analysis and relevance feedback
AU - Zhu, Guangyu
AU - Huang, Qingming
AU - Gong, Yihong
PY - 2008
Y1 - 2008
N2 - Most of existing work on sports video analysis concentrates on highlight extraction. Few efforts devoted to the important issue as how to organize the extracted highlights which is adapt for the user preference. In this paper, we propose a novel approach to rank the highlights extracted from broadcast tennis video based on multi-modality analysis and relevance feedback. Firstly, visual and auditory features are employed to construct the mid-level representations for the content of broadcast tennis video. Then, the affective features are extracted from mid-level representations and the multiple ranking models are built using nonlinear regression algorithm. Finally, the ranking models are linearly combined to generate the final highlight ranking results. The relevance feedback technique is employed to effectively capture the user interest in visual and auditory attention spaces to adjust the ranking results being suitable to the user preference. The experimental results are encouraging and demonstrate that our approach is effective.
AB - Most of existing work on sports video analysis concentrates on highlight extraction. Few efforts devoted to the important issue as how to organize the extracted highlights which is adapt for the user preference. In this paper, we propose a novel approach to rank the highlights extracted from broadcast tennis video based on multi-modality analysis and relevance feedback. Firstly, visual and auditory features are employed to construct the mid-level representations for the content of broadcast tennis video. Then, the affective features are extracted from mid-level representations and the multiple ranking models are built using nonlinear regression algorithm. Finally, the ranking models are linearly combined to generate the final highlight ranking results. The relevance feedback technique is employed to effectively capture the user interest in visual and auditory attention spaces to adjust the ranking results being suitable to the user preference. The experimental results are encouraging and demonstrate that our approach is effective.
KW - Highlight ranking
KW - Multi-modality analysis
KW - Relevance feedback
KW - Sports video analysis
UR - https://www.scopus.com/pages/publications/70350632803
U2 - 10.1007/978-3-540-89796-5_69
DO - 10.1007/978-3-540-89796-5_69
M3 - 会议稿件
AN - SCOPUS:70350632803
SN - 354089795X
SN - 9783540897958
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 675
EP - 684
BT - Advances in Multimedia Information Processing - PCM 2008 - 9th Pacific Rim Conference on Multimedia, Proceedings
T2 - 9th Pacific Rim Conference on Multimedia, PCM 2008
Y2 - 9 December 2008 through 13 December 2008
ER -