西安交通大学电子与信息工程学院,西安,710049
网络首发:2009-06-10,
纸质出版:2009
移动端阅览
王国珲, 韩九强, 贾洪海, 等. 一种从明暗恢复形状的快速黏性解算法[J]. 西安交通大学学报, 2009,43(6):43-47.
A Fast Viscosity Solution Algorithm for Shape from Shading[J]. 2009, 43(6): 43-47.
针对传统的从明暗恢复形状(SFS)算法存在误差大、耗时长的问题
提出了一种SFS的快速黏性解算法(PSFS-FVS).首先假定物体表面反射模型为朗伯模型
建立透视投影下的图像辐照度方程
然后将该方程转化为包含物体表面深度信息的静态Hamilton-Jacobi偏微分方程
使用非线性规划原理逼近该微分方程的黏性解
进而得到物体表面的三维形状.合成花瓶图像的实验结果表明:与Prados-Faugeras算法相比
PSFS-FVS算法在相同迭代次数时
恢复三维形状高度的平均相对误差降低了8.7%; 在相同的误差条件下
所需的CPU运行时间减少了23.5%.实际人脸图像的三维形状恢复结果表明
PSFS-FVS算法在恢复局部细节信息时更加准确有效.
Focusing on the high error and time consuming of the algorithms for shape from shading(SFS)
a fast viscosity solution algorithm of perspective SFS(PSFS-FVS)is proposed. The image irradiance equation is established on the basis of Lambertian reflectance model and perspective camera projection. Then the equation is transformed into a static Hamilton-Jacobi partial differential equation(PDE)that contains the shape information of a surface. The viscosity solution of the resulting PDE is approximated by using a nonlinear programming method
and then the surface shape is generated. Experimental results and comparisons with the Prados-Faugeras algorithm on synthetic vase image show that the mean relative error of the height of the PSFS-FVS algorithm is reduced by 8.7% with the same iterations
and the CPU time of the PSFS-FVS algorithm is decreased by 23.5% at the same error
respectively. Reconstruction results from real face image show that the PSFS-FVS algorithm is more accurate and effective than the Prados-Faugeras algorithm in dealing with the local of the surface.
HORN B K P. Height and gradient from shading [J]. International Journal of Computer Vision, 1990, 5(1): 37-75.
ZHANG R, TSAI P S, CRYER J E, et al. Shape from shading: a survey [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1999, 21(8): 690-706.
DUROU J D, FALCONE M, SAGONA M. Numerical methods for shape-from-shading: a new survey with benchmarks [J]. Computer Vision and Image Understanding, 2008, 109(1): 22-43.
杨磊,韩九强.一种由明暗恢复形状的改进变分算法[J].西安交通大学学报,2008,42(4):418-422.
YANG Lei, HAN Jiuqiang. Improved variational algorithm of shape-from-shading [J]. Journal of Xi'an Jiaotong University, 2008, 42(4): 418-422.
ROUY E, TOURIN A. A viscosity solutions approach to shape-from-shading [J]. SIAM Journal on Numerical Analysis, 1992, 29(3): 867-884.
PRADOS E, FAUGERAS O. Shape from shading: a well-posed problem? [C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Los Alamitos, CA, USA: IEEE Computer Society, 2005: 870-877.
PRADOS E, FAUGERAS O, CAMILLI F. Shape from shading: a well-posed problem, RR-5297 [R]. Paris, France: INRIA, 2004.
JIA Honghai, WANG Ying, HAN Jiuqiang, et al. Research on a new sfs shape recovery method based on perceptive model [C]∥Proceedings of the 10th Meeting on Image Recognition and Understanding. Tokyo, Japan: IEICE Information and System Society, 2007: 649-653.
PRADOS E, FAUGERAS O. A rigorous and realistic shape from shading method and some of its applications, RR-5133 [R]. Paris, France: INRIA, 2004.
PRADOS E, CAMILLI F, FAUGERAS O. A unifying and rigorous shape from shading method adapted to realistic data and applications [J]. Journal of Mathematical Imaging and Vision, 2006, 25(3): 307-328.
0
浏览量
4
下载量
3
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621