IEICE TRANSACTIONS on Information
Robust 3D Surface Reconstruction in Real-Time with Localization Sensor
Summary :
We present a system to improve the robustness of real-time 3D surface reconstruction by utilizing non-inertial localization sensor. Benefiting from such sensor, our easy-to-build system can effectively avoid tracking drift and lost comparing with conventional dense tracking and mapping systems. To best fusing the sensor, we first adopt a hand-eye calibration and performance analysis for our setup and then propose a novel optimization framework based on adaptive criterion function to improve the robustness as well as accuracy. We apply our system to several challenging reconstruction tasks, which show significant improvement in scanning robustness and reconstruction quality.
- Publication
- IEICE TRANSACTIONS on Information Vol.E101-D No.8 pp.2168-2172
- Publication Date
- 2018/08/01
- Publicized
- 2018/05/14
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2018EDL8056
- Type of Manuscript
- LETTER
- Category
- Image Recognition, Computer Vision
Authors
Wei LI
Nanjing University of Aeronautics and Astronautics
Yi WU
Nanjing University of Aeronautics and Astronautics
Chunlin SHEN
Nanjing University of Aeronautics and Astronautics
Huajun GONG
Nanjing University of Aeronautics and Astronautics
Keyword
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Wei LI, Yi WU, Chunlin SHEN, Huajun GONG, "Robust 3D Surface Reconstruction in Real-Time with Localization Sensor" in IEICE TRANSACTIONS on Information,
vol. E101-D, no. 8, pp. 2168-2172, August 2018, doi: 10.1587/transinf.2018EDL8056.
Abstract: We present a system to improve the robustness of real-time 3D surface reconstruction by utilizing non-inertial localization sensor. Benefiting from such sensor, our easy-to-build system can effectively avoid tracking drift and lost comparing with conventional dense tracking and mapping systems. To best fusing the sensor, we first adopt a hand-eye calibration and performance analysis for our setup and then propose a novel optimization framework based on adaptive criterion function to improve the robustness as well as accuracy. We apply our system to several challenging reconstruction tasks, which show significant improvement in scanning robustness and reconstruction quality.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDL8056/_p
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@ARTICLE{e101-d_8_2168,
author={Wei LI, Yi WU, Chunlin SHEN, Huajun GONG, },
journal={IEICE TRANSACTIONS on Information},
title={Robust 3D Surface Reconstruction in Real-Time with Localization Sensor},
year={2018},
volume={E101-D},
number={8},
pages={2168-2172},
abstract={We present a system to improve the robustness of real-time 3D surface reconstruction by utilizing non-inertial localization sensor. Benefiting from such sensor, our easy-to-build system can effectively avoid tracking drift and lost comparing with conventional dense tracking and mapping systems. To best fusing the sensor, we first adopt a hand-eye calibration and performance analysis for our setup and then propose a novel optimization framework based on adaptive criterion function to improve the robustness as well as accuracy. We apply our system to several challenging reconstruction tasks, which show significant improvement in scanning robustness and reconstruction quality.},
keywords={},
doi={10.1587/transinf.2018EDL8056},
ISSN={1745-1361},
month={August},}
Copy
TY - JOUR
TI - Robust 3D Surface Reconstruction in Real-Time with Localization Sensor
T2 - IEICE TRANSACTIONS on Information
SP - 2168
EP - 2172
AU - Wei LI
AU - Yi WU
AU - Chunlin SHEN
AU - Huajun GONG
PY - 2018
DO - 10.1587/transinf.2018EDL8056
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E101-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2018
AB - We present a system to improve the robustness of real-time 3D surface reconstruction by utilizing non-inertial localization sensor. Benefiting from such sensor, our easy-to-build system can effectively avoid tracking drift and lost comparing with conventional dense tracking and mapping systems. To best fusing the sensor, we first adopt a hand-eye calibration and performance analysis for our setup and then propose a novel optimization framework based on adaptive criterion function to improve the robustness as well as accuracy. We apply our system to several challenging reconstruction tasks, which show significant improvement in scanning robustness and reconstruction quality.
ER -
English
