ACM Home Page
Please provide us with feedback. Feedback
NTU TRECVID-2007 fast rushes summarization system
Full text PdfPdf (818 KB)
Source
International Multimedia Conference archive
Proceedings of the international workshop on TRECVID video summarization table of contents
Augsburg, Bavaria, Germany
Pages: 74 - 78  
Year of Publication: 2007
ISBN:978-1-59593-780-3
Authors
Chen-Ming Pan  National Taiwan University, Taipei, Taiwan Roc
Yung-Yu Chuang  National Taiwan University, Taipei, Taiwan Roc
Winston H. Hsu  National Taiwan University, Taipei, Taiwan Roc
Sponsors
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
ACM: Association for Computing Machinery
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 1,   Downloads (12 Months): 28,   Citation Count: 4
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/10.1145/1290031.1290045
What is a DOI?

ABSTRACT

Rushes are the raw materials used to produce a video. They often contain redundant and repetitive contents. Rushes summarization aims to provide a quick overview for a rushes video. As part of TRECVID 2007, NIST initiates a rushes summarization task. This paper reports on the design of NTU rushes summarization system for this task. Our system consists of three components, shot segmentation, redundant shot detection and summary creation. To tackle the bulky rushes, we focus on efficient but effective feature representations (local color histograms and compressed-domain motion vectors) and summarization methods. In addition, we proposed a novel approach to detect clapper shots which are not only relevant to concise summarizes but also essential for indexing numerous camera takes in the rushes. Even practically efficient and requiring only 40% of the video time for computation, the proposed system achieved satisfying results in TRECVID 2007 rushes summarization task.


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
I. Koprinska and S. Carrato. Temporal video segmentation: A survey. 16:477--500, 2001.
 
3
4
 
5
I. K. Sethi and N. V. Patel. Statistical approach to scene change detection. In Storage and Retrieval for Image and Video Databases (SPIE), pages 329--338, 1995.


Collaborative Colleagues:
Chen-Ming Pan: colleagues
Yung-Yu Chuang: colleagues
Winston H. Hsu: colleagues