Mr. Jun Fujiki Profile

Jun Fujiki

Researcher at AIST

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Publications (7)

Proceedings Article | 11 March 2011 Paper

Improved methods for dewarping images in convex mirrors in fine art: applications to van Eyck and Parmigianino

Yumi Usami, David Stork, Jun Fujiki, Hideitsu Hino, Shotaro Akaho, Noboru Murata

Proceedings Volume 7869, 78690F (2011) https://doi.org/10.1117/12.873194

KEYWORDS: Mirrors, Optical spheres, Computer graphics, Spherical lenses, 3D modeling, Photography, 3D image processing, Coherence (optics), Image segmentation, Glasses

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We derive and demonstrate new methods for dewarping images depicted in convex mirrors in artwork and for estimating the three-dimensional shapes of the mirrors themselves. Previous methods were based on the assumption that mirrors were spherical or paraboloidal, an assumption unlikely to hold for hand-blown glass spheres used in early Renaissance art, such as Johannes van Eyck's Portrait of Giovanni (?) Arnolfini and his wife (1434) and Robert Campin's Portrait of St. John the Baptist and Heinrich von Werl (1438). Our methods are more general than such previous methods in that we assume merely that the mirror is radially symmetric and that there are straight lines (or colinear points) in the actual source scene. We express the mirror's shape as a mathematical series and pose the image dewarping task as that of estimating the coefficients in the series expansion. Central to our method is the plumbline principle: that the optimal coefficients are those that dewarp the mirror image so as to straighten lines that correspond to straight lines in the source scene. We solve for these coefficients algebraically through principal component analysis, PCA. Our method relies on a global figure of merit to balance warping errors throughout the image and it thereby reduces a reliance on the somewhat subjective criterion used in earlier methods. Our estimation can be applied to separate image annuli, which is appropriate if the mirror shape is irregular. Once we have found the optimal image dewarping, we compute the mirror shape by solving a differential equation based on the estimated dewarping function. We demonstrate our methods on the Arnolfini mirror and reveal a dewarped image superior to those found in prior work|an image noticeably more rectilinear throughout and having a more coherent geometrical perspective and vanishing points. Moreover, we find the mirror deviated from spherical and paraboloidal shape; this implies that it would have been useless as a concave projection mirror, as has been claimed. Our dewarped image can be compared to the geometry in the full Arnolfini painting; the geometrical agreement strongly suggests that van Eyck worked from an actual room, not, as has been suggested by some art historians, a "fictive" room of his imagination. We apply our method to other mirrors depicted in art, such as Parmigianino's Self-portrait in a convex mirror and compare our results to those from earlier computer graphics simulations.

Proceedings Article | 2 November 2001 Paper

Invariants from the three-dimensional vector autoregressive model

Jun Fujiki, Yasuhiko Kiuchi, Masaru Tanaka, Taketoshi Mishima

Proceedings Volume 4476, (2001) https://doi.org/10.1117/12.447269

KEYWORDS: 3D modeling, Autoregressive models, Data modeling, Feature extraction, Image understanding, Pattern recognition, Matrices, Mathematical modeling, Visual process modeling, 3D image processing

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Proceedings Article | 23 October 2000 Paper

Three-dimensional vector autoregressive coefficients

Jun Fujiki, Masaru Tanaka

Proceedings Volume 4117, (2000) https://doi.org/10.1117/12.404817

KEYWORDS: 3D modeling, Autoregressive models, Data modeling, Curium, Samarium, Feature extraction, Matrices, Image understanding, Americium, Pattern recognition

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Proceedings Article | 23 September 1999 Paper

Properties of the three-dimensional vector autoregressive model

Jun Fujiki, Masaru Tanaka

Proceedings Volume 3811, (1999) https://doi.org/10.1117/12.364097

KEYWORDS: Autoregressive models, 3D modeling, Data modeling, Americium, Radon, Pattern recognition, Promethium, Data compression, Visual process modeling, Image understanding

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Proceedings Article | 2 October 1998 Paper

Iterative factorization method for object recognition

Jun Fujiki, Takeshi Kurata, Masaru Tanaka

Proceedings Volume 3454, (1998) https://doi.org/10.1117/12.323255

KEYWORDS: Affine motion model, Cameras, Motion models, Iterative methods, Motion estimation, Motion measurement, 3D modeling, Principal component analysis, Error analysis, Object recognition

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Proceedings Article | 24 September 1998 Paper

Affine epipolar geometry via factorization method and its application

Takeshi Kurata, Jun Fujiki, Katsuhiko Sakaue

Proceedings Volume 3457, (1998) https://doi.org/10.1117/12.323437

KEYWORDS: Affine motion model, 3D modeling, Image restoration, 3D image reconstruction, 3D image processing, Motion models, Visual process modeling, Cameras, Mathematical modeling, Vector spaces

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Proceedings Article | 20 October 1997 Paper

Metric of affine shape and motion: the intuitive interpretation in terms of the factorization method

Jun Fujiki, Takeshi Kurata

Proceedings Volume 3168, (1997) https://doi.org/10.1117/12.279663

KEYWORDS: Cameras, Matrices

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Showing 5 of 7 publications

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