3D Reconstruction with circular light field by using 3D hough transformation

基于三维霍夫变换的环形光场三维重建

Received: 12 June 2020

Abstract

Aiming at the issue of incomplete trajectories in the 2D epipolar image of circular light field, this paper proposes a 3D reconstruction method by using 3D Hough transformation. This method computes 3D point clouds by computing the parameters of feature trajectories in 3D image volume. By analyzing the 3D distribution of circular light field trajectories, binary curves in image volume are extracted, and their local orientation are further estimated by the 3D structure tensor. The 3D Hough space generation and the parameter selection method are proposed to the 3D curves detection. The parameters of these curves are converted to 3D point clouds on each view and then merged to final 3D reconstruction. The ambiguity of Hough transformation solution on 2D epipolar image is overcome by the 3D analyzing method. The experiments are carried out on both synthetic and real datasets. The experiment results show that this method can improve the reconstruction performance compared with the state-of-the-art in circular light field.

摘要

针对环形光场的二维对极几何图特征轨迹不完整问题，提出了一种基于三维霍夫变换的环形光场三维重建方法。将三维重建参数求解转化为高维图像体特征轨迹参数的解算。通过分析环形光场图像体中特征轨迹三维分布，提取图像体中的轨迹曲线，并采用三维结构张量分析曲线的局部方向。构建了面向三维曲线检测的三维霍夫空间，并设计霍夫参数筛选方法。通过曲线参数恢复每个视点下的三维点云并根据环形光场视点关系融合形成重建结果。消除了二维霍夫变换求解三维特征轨迹参数的歧义性，并在环形光场仿真与真实数据集上进行了三维重建实验。实验结果表明，该方法能够提高环形光场三维重建的精度与效果。