An Augmented-Reality Holographic Stereogram Based on 3D Optical Field Information Manipulation and Reconstruction

Yunpeng Liu,Qian Yang,Ping Zhang,Xingpeng Yan,Xiaoyu Jiang,Qiang Qu,Tao Jing,Pei Li

doi:10.3389/fphy.2021.828825

Abstract

Holographic stereogram comprises a hotspot in the field of three-dimensional (3D) display. It can reconstruct the light field information of real and virtual scenes at the same time, further improving the comprehensibility of the scene and achieving the “augmentation” of the scene. In this paper, an augmented reality-holographic stereogram based on 3D reconstruction is proposed. First, the point cloud data is generated by VisualSFM software, and then the 3D mesh model is reconstructed by MeshLab software. The obtained scene model and virtual scene are rendered simultaneously to obtain the real and virtual fusion scene. Analysis of experimental results shows that the proposed method can effectively realize augmented reality-holographic stereogram.

Highlights

Holographic stereogram (HS) [1,2,3] comprises a research hotspot in the field of three-dimensional (3D) display, providing a flexible and efficient means of 3D display
We show and analyze the 3D information of the obtained hologram, including horizontal parallax, vertical parallax, and depth information
An augmented reality–holographic stereogram based on 3D reconstruction is proposed that provides an effective means for augmented holographic 3D display of a scene

Summary

INTRODUCTION

Holographic stereogram (HS) [1,2,3] comprises a research hotspot in the field of three-dimensional (3D) display, providing a flexible and efficient means of 3D display. To verify the effectiveness of the method, we used the 3D reconstruction technology based on multi-view map, which mainly depends on two software packages, i.e., VisualSFM and MeshLab. The fusion of real and virtual scenes depends on 3D Studio Max. VisualSFM uses a stereo-matching algorithm to detect and match the image feature points, uses a structure-frommotion (SFM) algorithm to calculate the pose of the camera in space according to the matching data and reconstructs the 3D point-cloud model of the 3D scene. The dense point cloud data were imported into MeshLab for operations such as removing miscellaneous points, meshing, repairing manifold edges, parameterization, and texturing, to FIGURE 10 | Vertical parallax information of the reconstructed image (A) Head up view (B) detail of (A) (C) bottom view, and (D) detail of (C).

Results and Analysis

CONCLUSION

DATA AVAILABILITY STATEMENT