A real-time voxel 3D reconstruction based on disparity estimation combined with SLAM

Zenan Lin; Xue Wan; Yuanbin Shao

doi:10.1117/12.2645676

23 August 2022 A real-time voxel 3D reconstruction based on disparity estimation combined with SLAM

Zenan Lin, Xue Wan, Yuanbin Shao

Proceedings Volume 12305, International Symposium on Artificial Intelligence Control and Application Technology (AICAT 2022); 123050K (2022) https://doi.org/10.1117/12.2645676
Event: International Symposium on Artificial Intelligence Control and Application Technology (AICAT 2022), 2022, Hangzhou, China

Abstract

Dense 3D reconstruction is crucial in the field of intelligent robot, drone application, and intelligent control. However, most state-of-the-art real-time dense 3D reconstruction methods require depth camera. In this paper, we propose a real-time dense voxel 3D reconstruction method that relies only on binocular cameras without depth sensors. Our method is based on binocular disparity estimation and sparse pose estimation and can be dynamic adjusted while the keyframe pose changes in SLAM(Simultaneous Localization and Mapping) system. Our result can be used for path planning and control of robots and vehicles. Experiments on our virtual dataset and KITTI benchmark show that our method can achieve real-time performance of 5~10Hz and localization accuracy of 0.107(Chamfer Distance).

Citation Download Citation

Zenan Lin, Xue Wan, and Yuanbin Shao "A real-time voxel 3D reconstruction based on disparity estimation combined with SLAM", Proc. SPIE 12305, International Symposium on Artificial Intelligence Control and Application Technology (AICAT 2022), 123050K (23 August 2022); https://doi.org/10.1117/12.2645676

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