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A computational theory of visible-surface representations is developed. The visible-surface reconstruction process that computes these quantitative representations unifies formal solutions to the key problems of: (1) integrating multiscale constraints on surface depth and orientation from multiple-visual sources; (2) interpolating dense, piecewise-smooth surfaces from these constraints; (3) detecting surface depth and orientation discontinuities to apply boundary conditions on interpolation; and (4) structuring large-scale, distributed-surface representations to achieve computational efficiency. Visible-surface reconstruction is an inverse problem. A well-posed variational formulation results from the use of a controlled-continuity surface model. Discontinuity detection amounts to the identification of this generic model's distributed parameters from the data. Finite-element shape primitives yield a local discretization of the variational principle. The result is an efficient algorithm for visible-surface reconstruction.>
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Demetri Terzopoulos (Fri,) studied this question.
synapsesocial.com/papers/6a1564de5347fbb1739fb662 — DOI: https://doi.org/10.1109/34.3908
Demetri Terzopoulos
University of Central Florida
IEEE Transactions on Pattern Analysis and Machine Intelligence
Schlumberger (United States)
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