Statistical analysis and transfer of coarse-grain pictorial style
Name
70081070-MIT.pdf
Description
Full printable version
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14.86 MB
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Checksum (MD5)
008d548835593ffefd356fdf86a3b6a5
Author(s)
Bae, Soonmin
Advisor(s)
Frédo Durand.
Date Issued
2005
Publisher
Massachusetts Institute of Technology
Abstract
We show that image statistics can be used to analyze and transfer simple notions of pictorial style of paintings and photographs. We characterize the frequency content of pictorial styles, such as multi-scale, spatial variations, and anisotropy properties, using a multi-scale and oriented decomposition, the steerable pyramid. We show that the average of the absolute steerable coefficients as a function of scale characterizes simple notions of "look" or style. We extend this approach to account for image non-stationarity, that is, we capture and transfer the spatial variations of multi-scale content. In addition, we measure the standard deviation of the steerable coefficients across orientation, which characterizes image anisotropy and permits analysis and transfer of oriented structures. We focus on the statistical features that can be transferred. Since we couple analysis and transfer, our statistical model and transfer tools are consistent with the visual effect of pictorial styles. For this reason, our technique leads to more intuitive manipulation and interpolation of pictorial styles. In addition, our statistical model can be used to classify and retrieve images by style.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.
Includes bibliographical references (p. 96-103).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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