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[SG+04b]  Is that a Smile? Gaze Dependent Facial Expressions

Setlur:2004:ITS (In proceedings)
Author(s)Setlur V. and Gooch B.
Title« Is that a Smile? Gaze Dependent Facial Expressions »
InProceedings of the Third International Symposium on Non-Photorealistic Animation and Rendering (NPAR 2004, Annecy, France, June 7--9, 2004)
Editor(s)Aaron Hertzmann and Craig Kaplan
Page(s)79--84
Year2004
PublisherACM Press
AddressNew York
Editor(s)Aaron Hertzmann and Craig Kaplan

Abstract
Using artistic methods for manipulating perception as a basis, we present a technique that creates facial images with conflicting emotional states at different spatial frequencies. The foveal and peripheral components of the human visual system tend to interpret the emotional state of the subject differently, adding a degree of elusiveness to facial image. The system first isolates the coarser low spatial frequency components and finer high spatial frequency details from two images with differing facial expressions. Our technique then performs image segmentation with edge detection, and morphs the images. In practice we have found that high spatial frequency elements determine the dominant expression in the resulting image, while the low spatial frequency elements contribute subtlety.

BibTeX code
@inproceedings{Setlur:2004:ITS,
  optorganization = {},
  author = {Vidya Setlur and Bruce Gooch},
  optkey = {},
  optseries = {},
  editor = {Aaron Hertzmann and Craig Kaplan},
  localfile = {papers/Setlur.2004.ITS.pdf},
  address = {New York},
  publisher = {ACM Press},
  optmonth = {},
  doi = {http://doi.acm.org/10.1145/987657.987670},
  opturl = {},
  optwww = {},
  optcrossref = {},
  booktitle = NPAR2004,
  optstatus = {},
  optvolume = {},
  optnumber = {},
  title = {{I}s that a {S}mile? {G}aze {D}ependent {F}acial {E}xpressions},
  abstract = {Using artistic methods for manipulating perception as a basis, we
              present a technique that creates facial images with conflicting
              emotional states at different spatial frequencies. The foveal and
              peripheral components of the human visual system tend to interpret
              the emotional state of the subject differently, adding a degree of
              elusiveness to facial image. The system first isolates the coarser
              low spatial frequency components and finer high spatial frequency
              details from two images with differing facial expressions. Our
              technique then performs image segmentation with edge detection,
              and morphs the images. In practice we have found that high spatial
              frequency elements determine the dominant expression in the
              resulting image, while the low spatial frequency elements
              contribute subtlety.},
  year = {2004},
  pages = {79--84},
}

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