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Painting with looks: photographic images from video using quantimetric processing
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Source International Multimedia Conference archive
Proceedings of the tenth ACM international conference on Multimedia table of contents
Juan-les-Pins, France
SESSION: Session 4: video processing and transformation table of contents
Pages: 117 - 126  
Year of Publication: 2002
ISBN:1-58113-620-X
Authors
Steve Mann  University of Toronto
Corey Manders  University of Toronto
James Fung  University of Toronto
Sponsors
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
SIGCOMM: ACM Special Interest Group on Data Communication
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 1,   Downloads (12 Months): 17,   Citation Count: 2
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ABSTRACT

When we ask the fundamental question "What does a camera measure?", we arrive at the concept of quantimetric imaging, which uses a new quantimetric unit, q, characteristic of a particular camera (e.g. each kind of camera defines its own quantimetric unit q based on its spectral response, etc.). Fluctuations in interframe exposures, along a sequence of images, give rise to a comparametric relationship between successive pairs of images. This allows us to estimate the response function of the camera (to derive the quantimetric unit q) as well as the relative differences in exposure. A new method of video image processing that exploits multiple differently exposed pictures (frames of the video sequence) of overlapping subject matter is thus possible. The method may be used whenever a video camera having automatic exposure captures multiple frames of video with the same subject matter appearing in regions of overlap between at least some of the successive video frames. Since almost all cameras have an automatic exposure feature, typically center weighted, when a light object falls in the center of the frame the exposure is automatically decreased, whereas the exposure is automatically increased when the camera swings around to point at a darker object. Such fluctuations in gain may be used to estimate the camera's response function, to estimate exposure differences, to do quantimetric processing, as well as to obtain images having both extended dynamic range and extended dynamic domain.


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
Candocia, F. M. (2002). Synthesizing a panoramic scene with a common exposure via the simultaneous registration of images. FCRAR. avail. at http://iul.eng.fiu.edu/candocia/Publications/Publications.htm.
 
2
de Boor, C. (1978). A Practical Guide to Splines, volume 27 of Applied Mathematical Series. Springer-Verlag. ISBN 0-387-90356-9.
 
3
Galton, F. (1886). Regression towards mediocrity in hereditary stature. http://www.jmpdiscovery.com/news/jmpercable/ summer98/regression.html.
 
4
Mann, S. (1998). Humanistic intelligence/humanistic computing: 'wearcomp' as a new framework for intelligent signal processing. Proceedings of the IEEE, 86(11):2123--2151+cover. http://wearcam.org/procieee.htm.
 
5


Collaborative Colleagues:
Steve Mann: colleagues
Corey Manders: colleagues
James Fung: colleagues