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Description: shapeletsurf.m :通过表面法向量重建三维表面；
frankotchellappa.m：用Frankot and Chellappa的算法重建可积性三维表面；
grad2slanttilt.m:根据梯度值求取slant 和tilt角；
slanttilt2grad.m ：根据slant 和tilt角度求三维表面的梯度。
详尽的可见压缩文件中的说明-shapeletsurf.m : France Vector surface reconstruction of 3D surface; frankotchellappa.m : Chellappa with Frankot and reconstruction algorithms can plot three-dimensional surface; grad2slanttilt.m : gradient values strike slant and tilt angle; slanttilt2grad.m : slant and the tilt angle for 3D surface gradient. Detailed Visibility compressed files of note
Platform: |
Size: 12977 |
Author: 陈亨利 |
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Description: shapeletsurf.m :通过表面法向量重建三维表面；
frankotchellappa.m：用Frankot and Chellappa的算法重建可积性三维表面；
grad2slanttilt.m:根据梯度值求取slant 和tilt角；
slanttilt2grad.m ：根据slant 和tilt角度求三维表面的梯度。
详尽的可见压缩文件中的说明-shapeletsurf.m : France Vector surface reconstruction of 3D surface; frankotchellappa.m : Chellappa with Frankot and reconstruction algorithms can plot three-dimensional surface; grad2slanttilt.m : gradient values strike slant and tilt angle; slanttilt2grad.m : slant and the tilt angle for 3D surface gradient. Detailed Visibility compressed files of note
Platform: |
Size: 12288 |
Author: 陈亨利 |
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Description: An implementation of Frankot and Chellappa a algorithm for constructing an integrable surface from gradient information.
matlab file
Platform: |
Size: 1024 |
Author: dhlee |
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Description: 从2D梯度域进行表面重建
包含快速的泊松方程解法-A fast 2D Poisson Solver in Matlab using Neumann Boundary conditions
,
Implementation of Frankot-Chellappa Algorithm,
Robust surface reconstruction using M-estimators,
Anisotropic surface reconstruction
Platform: |
Size: 17408 |
Author: wang si |
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Description: Function reconstructs an estimate of a surface from its surface normals by correlating the surface normals with that those of a bank of shapelet basis functions. The correlation results are summed to produce the reconstruction. The sumation of shapelet basis functions results in an implicit integration of the surface while enforcing surface continuity.
Note that the reconstruction is only valid up to a scale factor (which can be corrected for). However the reconstruction process is very robust to noise and to missing data values. Reconstructions (up to positive/negative shape ambiguity) are possible where there is an ambiguity of pi in tilt values. Low quality reconstructions are also possible with just slant, or just tilt data alone. However, if you have full gradient information you are better off with the Frankot Chellappa algorithm below.
Platform: |
Size: 3072 |
Author: seshu babu v |
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Description: We propose a generalized equation to represent a continuum of surface
reconstruction solutions of a given non-integrable gradient field. We show
that common approaches such as Poisson solver and Frankot-Chellappa algorithm
are special cases of this generalized equation.
Platform: |
Size: 2405376 |
Author: 孙婷 |
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Description: 三维图像表面高度恢复算法，采用Frankot-Chellappa 全局积分算法进行表面三维构造的重建-Three dimensional image surface height restoration algorithm, the use of Frankot-Chellappa global integral algorithm for three-dimensional reconstruction of the surface
Platform: |
Size: 51200 |
Author: 杨永利 |
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