DocumentCode :
245930
Title :
A New Segmentation Method for Broadcast Sports Video
Author :
Hao Sun ; Chen, Jim X. ; Wechsler, Harry ; Yongquan Jiang
Author_Institution :
Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA
fYear :
2014
fDate :
19-21 Dec. 2014
Firstpage :
1789
Lastpage :
1793
Abstract :
We introduce a novel method, named S-CRP (Segmentation based on distance dependent Chinese Restaurant Process), to segment broadcast sports videos into semantic shots. S-CRP employs distance dependent Chinese Restaurant Process (DCRP) using two segmentation criteria, namely appearance and time distances. It takes advantage of the customer (frame) assignments in DCRP and is able to reduce the negative effect of noisy frames without the use of domain knowledge and more sophisticated classifiers. In addition, we find that the conventional performance evaluation metrics are unable to reflect the quality of the segmentation properly. We introduced a new performance metric, namely Levenshtein distance Ratio, which gives a more accurate measure of how well the segmentation result can match the original video structure.
Keywords :
image segmentation; sport; video signal processing; Levenshtein distance ratio; S-CRP method; appearance criteria; broadcast sports video; domain knowledge; performance evaluation metrics; segmentation based on distance dependent Chinese restaurant process; segmentation criteria; segmentation quality; semantic shots; time distance criteria; video segmentation method; Accuracy; Multimedia communication; Noise measurement; Semantics; Streaming media; Support vector machines; CRP; L-Ratio; sports video segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-7980-6
Type :
conf
DOI :
10.1109/CSE.2014.328
Filename :
7023839
Link To Document :
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