Xie Wuyuan, Nie Ying, Song Zhan, Wang Charlie C L
IEEE Comput Graph Appl. 2019 May-Jun;39(3):73-85. doi: 10.1109/MCG.2019.2909360. Epub 2019 Apr 4.
We tackle the problem of dense reconstruction with a practical system, in which near point lighting (NPL) is employed. Different from the conventional formulation of photometric stereo (PS) that assumes parallel lighting, PS under the NPL condition is a nonlinear problem as the local surface normals are coupled with its distance to the camera as well as the light sources. After obtaining the locations of point lights by a calibration process, we develop a new framework to solve this nonlinear reconstruction problem via mesh deformation, in which each facet is corresponding to a pixel in the image captured by the camera. In our framework, mesh deformation is decoupled into an iteration of interlaced steps of local projection and global blending. Experimental results verify that our method can generate accurate estimation of surface shape under NPL in a few iterations. Besides, this approach is robust to errors on the positions of light sources and is easy to be implemented.
我们使用一个实际系统来解决密集重建问题，该系统采用近点照明（NPL）。与传统的假设平行照明的光度立体（PS）公式不同，在NPL条件下的PS是一个非线性问题，因为局部表面法线与其到相机以及光源的距离相关联。通过校准过程获得点光源的位置后，我们开发了一个新框架，通过网格变形来解决这个非线性重建问题，其中每个小平面都对应于相机拍摄图像中的一个像素。在我们的框架中，网格变形被解耦为局部投影和全局混合的交错步骤的迭代。实验结果验证了我们的方法能够在几次迭代中对NPL下的表面形状生成准确估计。此外，这种方法对光源位置的误差具有鲁棒性，并且易于实现。
