Big little icons
Research output: Contribution to journal › Conference article › Research › peer-review
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Big little icons. / Rabaud, Vincent; Belongie, Serge.
In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2005.Research output: Contribution to journal › Conference article › Research › peer-review
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TY - GEN
T1 - Big little icons
AU - Rabaud, Vincent
AU - Belongie, Serge
N1 - Funding Information: This work was funded by the UCSD division of Calit2, the California Institute for Telecommunications and Information Technology, NSF-CAREER #0448615, DOE/LLNL contract no. W-7405-ENG-48 (subcontracts B542001 and B547328), and the Alfred P. Sloan Fellowship. The authors would also like to thank S. Agarwal, K. Branson, S. Das-gupta and A. Rabinovich for helpful discussions. Publisher Copyright: © 2005 IEEE Computer Society. All rights reserved.
PY - 2005
Y1 - 2005
N2 - Computer icons are small artificial images designed to be perceived with minimal ambiguity by the human visual system. In order to make them easier to perceive by visually impaired people, we propose a solution to the superresolution problem for color bitmap icons in a manner that exploits the unique characteristics of this medium versus that of generic low resolution natural imagery. We propose an MRF-based solution that incorporates local models of luminance and color perception which lays the basis for a snake-based vectorization of the icon and demonstrates encouraging performance on a diverse set of icons.
AB - Computer icons are small artificial images designed to be perceived with minimal ambiguity by the human visual system. In order to make them easier to perceive by visually impaired people, we propose a solution to the superresolution problem for color bitmap icons in a manner that exploits the unique characteristics of this medium versus that of generic low resolution natural imagery. We propose an MRF-based solution that incorporates local models of luminance and color perception which lays the basis for a snake-based vectorization of the icon and demonstrates encouraging performance on a diverse set of icons.
UR - http://www.scopus.com/inward/record.url?scp=85047163748&partnerID=8YFLogxK
U2 - 10.1109/CVPR.2005.422
DO - 10.1109/CVPR.2005.422
M3 - Conference article
AN - SCOPUS:85047163748
JO - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
JF - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SN - 2160-7508
T2 - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops
Y2 - 21 September 2005 through 23 September 2005
ER -
ID: 302054379