Improve 3D shape reconstruction with dual-camera measurement fusion

Authors

Yuewen Zhu, University of WollongongFollow
Qinghua Guo, University of WollongongFollow
Jiangtao Xi, University of WollongongFollow
Yanguang Yu, University of WollongongFollow
Jun Tong, University of WollongongFollow

RIS ID

141931

Publication Details

Y. Zhu, Q. Guo, J. Xi, Y. Yu & J. Tong, "Improve 3D shape reconstruction with dual-camera measurement fusion," Proceedings of SPIE - The International Society for Optical Engineering, vol. 11189, pp. 11890D-1-11890D-6, 2019.

Abstract

© 2019 SPIE. In this work, we consider the problem of 3D shape reconstruction with a system with two cameras and one projector, which can be regarded as a composite system with two fringe projection profilometry (FPP) systems and one stereo vision (SV) system. Different from the active SV systems in the literature where FPP is used to assist SV to address the issue of corresponding matching, a new system is proposed in this paper by constructing a fusion cost function with the consideration of both FPP and SV triangulations, so that the measurements of the two cameras can be fused to achieve better measurement performance than that of the active SV and FPP. In addition, a message passing algorithm for 3D shape reconstruction with the system is developed by using the new cost function and exploiting the unknown correlation of object surfaces. Simulation results demonstrate that the proposed system can achieve considerable performance gain.