针对于视觉任务中表面光滑、低纹理的目标,由于其结构纹理信息的缺乏及高反光的特性,传统三维重建算法无法恢复物体有效的表面形状特征,提出了基于光学偏振成像的低纹理目标三维重建算法。该算法不依赖于目标表面的结构纹理信息,以求解Stokes参数来量化目标表面反射光偏振态,而后结合偏振—几何空间分析,估计目标表面的法向量分布,最后提出了多尺度Shapelets算子将法向量信息积分获取目标的有效深度信息,恢复目标的三维形状。实验结果表明,针对低纹理的高反光目标,该算法能快速准确地恢复其表面的三维形态,并且有效抑制镜面耀光和噪声的干扰,算法实时性高。

For textureless objects with smooth surfaces in vision tasks, conventional three-dimensional reconstruction methods cannot retrieve the valid shape information of surfaces due to the loss of structure-texture features and the high reflectance.This paper presents a 3D reconstruction algorithm for textureless objects based on optical polarization imaging, which does not rely on the structure-texture features of objects.Stokes vector is calculated to quantify the polarization states of the surface reflected light.Then, based on the analysis of polarimetric-geometric space, the normal distribution of surface is effectively estimated.Finally, the multi-scale Shapelets blank operator is applied to integrate the normal vector to derive the accurate depth information of the objects.Experiments show that the proposed method can obtain the correct 3D shape reconstruction results, especially for high-reflective objects with less texture features.Meanwhile, the proposed technique can suppress the specular highlight and noise, with high computational efficiency.