ACM Home Page
Please provide us with feedback. Feedback
THU-intel at rushes summarization of TRECVID 2008
Full text PdfPdf (182 KB)
Source
International Multimedia Conference archive
Proceedings of the 2nd ACM TRECVid Video Summarization Workshop table of contents
Vancouver, British Columbia, Canada
Pages 124-128  
Year of Publication: 2008
ISBN:978-1-60558-309-9
Authors
Tao Wang  Intel China Research Center, Beijing, China
Shangping Feng  Tsinghua University, Beijing, China
Patricia P. Wang  Intel China Research Center, Beijing, China
Wei Hu  Intel China Research Center, Beijing, China
Shuang Zhang  Tsinghua University, Beijing, China
Wei Zhang  Tsinghua University, Beijing, China
Yangzhou Du  Intel China Research Center, Beijing, China
Jianguo Li  Intel China Research Center, Beijing, China
Jianmin Li  Tsinghua University, Beijing, China
Yimin Zhang  Intel China Research Center, Beijing, China
Sponsors
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 4,   Downloads (12 Months): 54,   Citation Count: 1
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1463563.1463586
What is a DOI?

ABSTRACT

Video summary is an active research field to help users to grasp a whole video's content for efficient browsing and editing. In this paper, we describe our THU-Intel rushes summarization system in TRECVID2008. In our approach, we first extract low-level audiovisual features and parse the video into shots, sub-shots and 1-second video clips. Then we remove junk video clips with color-bar, near uniform-color and clapboard frames etc. To select video clips with main objects and events, we evaluate each clip's representative score by multimodal features of color, edge, motion, and audio etc. Finally, we construct the rushes video summary by iteratively selecting the most representative video clips and removing similar ones. Extensive experiments are carried out on 40 testing rushes videos. Good results demonstrate the effectiveness of the proposed method.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

1
2
3
4
 
5
Cong Li, Zhijian Ou, Wei hu, Tao Wang, Yimin Zhang, Caption-aided speech detection in videos, ICASSP 2008, pp141--144.
 
6
7
 
8
Li, Z., Schuster, G. M., Katsaggelos, A. K., Rate-Distortion Optimial Video Summary Generation, IEEE Trans. on Image Processing, 14(10), 2005.
9
 
10
 
11
P. Over, P., Smeaton, A.F. and Kelly, P., The TRECVID 2007 BBC Rushes Summarization Evaluation Pilot. In Proc. of the TRECVID Workshop on Video Summarization (TVS'07), ACM Multimedia, 2007.
 
12
Park, J. I., Yagi, N., Enami, K., Aizawa, K., Hatori, M., Estimation of camera parameters from image sequence for model-based video coding, CirSysVideo(4), No. 3, June 1994, pp. 288--296.
13
14
15
16
 
17
Yuan, J. H., Zheng, W. J., Chen, L., etc. Tsinghua University at TRECVID 2004: shot boundary detection and high-level feature extraction, In NIST workshop of TRECVID 2004.


Collaborative Colleagues:
Tao Wang: colleagues
Shangping Feng: colleagues
Patricia P. Wang: colleagues
Wei Hu: colleagues
Shuang Zhang: colleagues
Wei Zhang: colleagues
Yangzhou Du: colleagues
Jianguo Li: colleagues
Jianmin Li: colleagues
Yimin Zhang: colleagues