Least squares surface reconstruction from gradients: Direct algebraic methods with spectral, Tikhonov, and constrained regularization

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Least squares surface reconstruction from gradients: Direct algebraic methods with spectral, Tikhonov, and constrained regularization. / Harker, Matthew; O'Leary, Paul.
Proceedings of Computer Vision and Pattern Recognition (CVPR) 2011. 2011. S. 2529-2536.

Publikationen: Beitrag in Buch/Bericht/KonferenzbandBeitrag in Konferenzband

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Harker M, O'Leary P. Least squares surface reconstruction from gradients: Direct algebraic methods with spectral, Tikhonov, and constrained regularization. in Proceedings of Computer Vision and Pattern Recognition (CVPR) 2011. 2011. S. 2529-2536 doi: 10.1109/CVPR.2011.5995427

Bibtex - Download

@inproceedings{bd3608ebbef941f6915796c55b1266fb,
title = "Least squares surface reconstruction from gradients: Direct algebraic methods with spectral, Tikhonov, and constrained regularization",
author = "Matthew Harker and Paul O'Leary",
year = "2011",
doi = "10.1109/CVPR.2011.5995427",
language = "English",
pages = "2529--2536",
booktitle = "Proceedings of Computer Vision and Pattern Recognition (CVPR) 2011",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - Least squares surface reconstruction from gradients: Direct algebraic methods with spectral, Tikhonov, and constrained regularization

AU - Harker, Matthew

AU - O'Leary, Paul

PY - 2011

Y1 - 2011

U2 - 10.1109/CVPR.2011.5995427

DO - 10.1109/CVPR.2011.5995427

M3 - Conference contribution

SP - 2529

EP - 2536

BT - Proceedings of Computer Vision and Pattern Recognition (CVPR) 2011

ER -