基于SFS方法的三维重构及精度分析

从明暗恢复形状(SFS)是计算机视觉中三维重构问题的研究热点和难点之一,目前已有算法存在两个问题:1)选择的反射模型不符合物体表面的反射特性；2)引入的约束条件和求解过程过于复杂,求解速度慢,效率低。对SFS算法进行了详细分析,引入了朗伯特光照反射模型,对物体表面做球形假设,然后对图像做近似微分运算以求出高度函数,实现了利用单幅灰度图像恢复物体表面三维形状并仿真的数据处理方法,同时对传统线性化SFS算法和所提算法进行了实验验证,对两种模型的重构精度和算法的执行效率进行了比较和分析。实验仿真结果表明,在保证一定精度的前提下,所提算法的执行效率比传统算法高。

3D Reconstruction Based on SFS Method and Accuracy Analysis

The recovery from shading (SFS) is one of the research hotspots and difficulties in 3D reconstruction of computer vision.There are two problems in the algorithm,one is that the selected reflection model does not accord with the reflection characteristic of object surface,the other is that the constraints and the solution process are too complex,the solution is slow and has low efficiency.In this paper,the SFS algorithm was analyzed in detail,the Lambert illumination model was introduced,the spherical surface was assumed,and then the height function was obtained by the approximate differential operation.The 3D shape of the object surface can be recovered by using single gray image.The traditional linearized SFS algorithm and the algorithm proposed in this paper were experimentally validated.The reconstruction precision and efficiency of the two models were compared and analyzed.Experimental results show that the proposed algorithm is more efficient than the traditional algorithm in ensuring certain accuracy.