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Gaze-based interaction for semi-automatic photo cropping
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Proceedings of the SIGCHI conference on Human Factors in computing systems table of contents
Montréal, Québec, Canada
SESSION: Collecting and editing photos table of contents
Pages: 771 - 780  
Year of Publication: 2006
ISBN:1-59593-372-7
Authors
Anthony Santella  Rutgers University, Piscataway, NJ
Maneesh Agrawala  UC Berkeley Computer Science, Berkeley, CA
Doug DeCarlo  Rutgers University, Piscataway, NJ
David Salesin  Adobe Systems and University of Washington, Seattle, WA
Michael Cohen  Microsoft Research, Redmond, WA
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

We present an interactive method for cropping photographs given minimal information about important content location, provided by eye tracking. Cropping is formulated in a general optimization framework that facilitates adding new composition rules, and adapting the system to particular applications. Our system uses fixation data</ to identify important image content and compute the best crop for any given aspect ratio or size, enabling applications such as automatic snapshot recomposition, adaptive documents, and thumbnailing. We validate our approach with studies in which users compare our crops to ones produced by hand and by a completely automatic approach. Experiments show that viewers prefer our gaze-based crops to uncropped images and fully automatic crops.


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
Arnheim, R. Art and Visual Perception. University of California Press, 1974.
 
2
Arnheim, R. The Power of the Center. University of California Press, 1988.
 
3
Banerjee, S. Composition Guided Image Aquisition. PhD thesis, University of Texas at Austin, 2004.
 
4
Byers, Z., Dixon, M., Smart, W. D., and Grimm, C. M. Say cheese!: Experiences with a robot photographer. Proceedings of the Fifteenth Innovative Applications of Artificial Intelligence Conference (IAAI-03), Acapulco, Mexico.
 
5
Chen, L., Xie, X., Fan, X., Ma, W., Shang, H., and Zhou, H. A visual attention mode for adapting images on small displays. MSR-TR-2002-125 Microsoft Research, Redmond, WA (2002).
 
6
7
 
8
David, H. A. The method of paired comparisons. Charles Griffin and Company, London, 1969.
9
 
10
Duchowski, A. Acuity-matching resolution degradation through wavelet coefficient scaling. IEEE Trans. on Image Processing 9, 8 (2000), 1437--1440.
 
11
 
12
 
13
Graham, D. Composing Pictures. Van Nostrand Reinhold, 1970.
 
14
Grill, T., and Scanlon, M. Photographic Composition Guidelines for Total image control through effective design. AMPHOTO, 1988.
 
15
Itti, L., and Koch, C. A saliency-based search mechanism for overt and covert shifts of visual attention. Vision Research 40 (2000), 1489--1506.
 
16
 
17
Jacob, R. J. Eye-movement-based human-computer interaction techniques: Toward non-command interfaces. 151--190.
18
 
19
Kendall, M. G. On the method of paired comparisons. Biometrika 31 (1940), 324 --345.
 
20
21
 
22
Locher, P. J. The contribution of eye-movement research to an understanding of the nature of pictorial balance perception: a review of the literature. Empirical Studies of the Arts 14, 2 (1996), 146--163.
 
23
Locher, P. J., Stappers, P. J., and Overbeeke, K. The role of balance as an organizing design principle underlying adults' compositional strategies for creating visual displays. Acta Psychologica 99 (1998), 141--161.
 
24
Locher, P. J., Stappers, P. J., and Overbeeke, K. An empirical evaluation of the visual rightness theory of pictorial composition. Acta Psychologica 103 (1999), 261--280.
25
 
26
McManus, I., Edmondson, D., and Rodgers, J. Balance in pictures. British Journal of Psychology 76 (1985), 73--94.
 
27
Peterson, B. Learning to see Creatively: How to compose great photographs. AMPHOTO, 1988.
 
28
Setlur, V., Takagi, S., Raskar, R., Gleicher, M., and Gooch, B. Automatic image retargeting. ACM SIGGRAPH Technical Sketch.
29
30
31

CITED BY  14

Collaborative Colleagues:
Anthony Santella: colleagues
Maneesh Agrawala: colleagues
Doug DeCarlo: colleagues
David Salesin: colleagues
Michael Cohen: colleagues