Specular highlight reduction with known surface geometry
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 132-144 |
Journal / Publication | Computer Vision and Image Understanding |
Volume | 168 |
Online published | 27 Oct 2017 |
Publication status | Published - Mar 2018 |
Link(s)
Abstract
The separation of reflection components is an important issue in computer graphics, computer vision, and image processing. This is a highly ill-posed problem since the number of unknowns to solve is much larger than the number of equations. We present a method to reduce the difficulty of this problem by assuming that surface geometry is known. A novel objective function based on robust principal component analysis is proposed to simultaneously separate specularities and estimate the position of light source. We develop an Augmented Lagrangian Multiplier based algorithm to solve the objective function efficiently and effectively. Experimental results on real-world and synthetic data demonstrate the effectiveness of our method.
Research Area(s)
- 3D geometry, Diffuse reflection, Robust PCA, Specular reflection
Citation Format(s)
Specular highlight reduction with known surface geometry. / Wei, Xing; Xu, Xiaobin; Zhang, Jiawei et al.
In: Computer Vision and Image Understanding, Vol. 168, 03.2018, p. 132-144.
In: Computer Vision and Image Understanding, Vol. 168, 03.2018, p. 132-144.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review