ACM Home Page
Please provide us with feedback. Feedback
Multi-scale video cropping
Full text PdfPdf (468 KB)
Source
International Multimedia Conference archive
Proceedings of the 15th international conference on Multimedia table of contents
Augsburg, Germany
SESSION: Applications 1 - enhancing user experiences table of contents
Pages: 97 - 106  
Year of Publication: 2007
ISBN:978-1-59593-702-5
Authors
Hazem El-Alfy  University of Maryland, College Park, MD
David Jacobs  University of Maryland, College Park, MD
Larry Davis  University of Maryland, College Park, MD
Sponsors
ACM: Association for Computing Machinery
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 70,   Citation Count: 0
Additional Information:

abstract   references   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/10.1145/1291233.1291255
What is a DOI?

ABSTRACT

We consider the problem of cropping surveillance videos. This process chooses a trajectory that a small sub-window can take through the video, selecting the most important parts of the video for display on a smaller monitor. We model the information content of the video simply, by whether the image changes at each pixel. Then we show that we can find the globally optimal trajectory for a cropping window by using a shortest path algorithm. In practice, we can speed up this process without affecting the results, by stitching together trajectories computed over short intervals. This also reduces system latency. We then show that we can use a second shortest path formulation to find good cuts from one trajectory to another, improving coverage of interesting events in the video. We describe additional techniques to improve the quality and efficiency of the algorithm, and show results on surveillance videos.


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
L.-Q. Chen, X. Xie, X. Fan, W.-Y. Ma, H.-J. Zhang, and H.-Q. Zhou. A visual attention model for adapting images on small displays. Multimedia Systems, 9(4):353--364, Oct 2003.
3
4
 
5
E. W. Dijkstra. A note on two problems in connection with graphs. Numerische Mathematik, 1:269--271, 1959.
6
 
7
A. Girgensohn, J. Adcock, M. Cooper, J. Foote, and L. Wilcox. Simplifying the management of large photo collections. In Human-computer Interaction (INTERACT'03), pages 196--203, 2003.
8
 
9
H. Hung and S. Gong. Quantifying temporal saliency. British Machine Vision Conference (BMVC '04), pages 727--736, Sept. 2004.
 
10
 
11
 
12
 
13
14
15
 
16
 
17
J. Wang, M. J. Reinders, R. L. Lagendijk, J. Lindenberg, and M. S. Kankanhalli. Video content representation on tiny devices. IEEE International Conference on Multimedia and Expo (ICME'04), 3:1711--1714, June 2004.
18

Collaborative Colleagues:
Hazem El-Alfy: colleagues
David Jacobs: colleagues
Larry Davis: colleagues