We propose a novel view path-planning method based on an online Multi-View Stereo (MVS) system. This method aims to incrementally construct the target three-dimensional (3D) model in real time. View paths are continually planned based on online feedback from the partially constructed model. The obtained paths fully cover low-quality surfaces while maximizing the reconstruction performance of MVS. Experimental results demonstrate that the proposed method can construct high quality 3D models with one exploration trial, without any re-scanning trial as in the explore-then-exploit method.

 

 

Related publications

1. S Song, D Kim, S Choi, View Path Planning via Online Multi-View Stereo for 3D Modeling of Large-Scale Structures, IEEE Transactions on Robotics, Accepted. [VIDEO]

2. KT Giang, S Song, D Kim, S Choi, Sequential Depth Completion with Confidence Estimation for 3D Model Reconstruction, IEEE RA-L, 6(2) : 327- 334, 2021 [LINK] [PDF] [VIDEO]

3. S Song, D Kim, S Jo, Active 3D modeling via online multi-view stereo, 2020 IEEE International Conference on Robotics and Automation (ICRA) [LINK] [PDF]

Categories: Robotic Intelligence