TY - GEN
T1 - Active 3D Modeling via Online Multi-View Stereo
AU - Song, Soohwan
AU - Kim, Daekyum
AU - Jo, Sungho
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - Multi-view stereo (MVS) algorithms have been commonly used to model large-scale structures. When processing MVS, image acquisition is an important issue because its reconstruction quality depends heavily on the acquired images. Recently, an explore-then-exploit strategy has been used to acquire images for MVS. This method first constructs a coarse model by exploring an entire scene using a pre-allocated camera trajectory. Then, it rescans the unreconstructed regions from the coarse model. However, this strategy is inefficient because of the frequent overlap of the initial and rescanning trajectories. Furthermore, given the complete coverage of images, MVS algorithms do not guarantee an accurate reconstruction result.In this study, we propose a novel view path-planning method based on an online 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 feedbacks 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 rescanning trial as in the explore-then-exploit method.
AB - Multi-view stereo (MVS) algorithms have been commonly used to model large-scale structures. When processing MVS, image acquisition is an important issue because its reconstruction quality depends heavily on the acquired images. Recently, an explore-then-exploit strategy has been used to acquire images for MVS. This method first constructs a coarse model by exploring an entire scene using a pre-allocated camera trajectory. Then, it rescans the unreconstructed regions from the coarse model. However, this strategy is inefficient because of the frequent overlap of the initial and rescanning trajectories. Furthermore, given the complete coverage of images, MVS algorithms do not guarantee an accurate reconstruction result.In this study, we propose a novel view path-planning method based on an online 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 feedbacks 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 rescanning trial as in the explore-then-exploit method.
UR - http://www.scopus.com/inward/record.url?scp=85089257697&partnerID=8YFLogxK
U2 - 10.1109/ICRA40945.2020.9197089
DO - 10.1109/ICRA40945.2020.9197089
M3 - Conference contribution
AN - SCOPUS:85089257697
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 5284
EP - 5291
BT - 2020 IEEE International Conference on Robotics and Automation, ICRA 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Robotics and Automation, ICRA 2020
Y2 - 31 May 2020 through 31 August 2020
ER -