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

Research output: Contribution to conference › Poster › Research › peer-review

34 Citations (Scopus)

Translated title of the contribution	Least squares surface reconstruction from gradients: Direct algebraic methods with spectral, Tikhonov, and constrained regularization
Original language	English
Publication status	Published - 2011
Event	IEEE Conference on Computer Vision and Pattern Recognition (CVPR) - Colorado Springs, United States Duration: 20 Jun 2011 → 25 Jun 2011

Conference	IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Country/Territory	United States
City	Colorado Springs
Period	20/06/11 → 25/06/11

Cite this

@conference{a90fd0cdc4d041e1af9726d4ff130567,

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",

language = "English",

note = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR) ; Conference date: 20-06-2011 Through 25-06-2011",

}

Least squares surface reconstruction from gradients: Direct algebraic methods with spectral, Tikhonov, and constrained regularization. / Harker, Matthew; O'Leary, Paul.
2011. Poster session presented at IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, Colorado, United States.

Research output: Contribution to conference › Poster › Research › peer-review