@inproceedings{421c1d374e7842daa11a60a77c11a494,
title = "Pose estimation for multi-camera systems",
abstract = "We build a multi-camera platform and present a relevant approach for pose estimation of the multi-camera system with known internal camera parameters. The proposed approach is able to solve the pose estimation, for a three-camera system that main camera has overlapping views with the left camera and the right camera respectively. By taking advantage of the optical flow method and the key frame policy to track the feature points, using Kalman filter (KF) to manage 3D points and adopting bundle adjustment (BA) to optimize the pose of the main camera, the experiment shows that the pose estimation results of the multi-camera system have good robustness.",
keywords = "BA, Multi-camera, Optical flow, Pose estimation, Simultaneous localization and mapping (SLAM)",
author = "Chunhui Zhao and Bin Fan and Jinwen Hu and Limin Tian and Zhiyuan Zhang and Sijia Li and Quan Pan",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Unmanned Systems, ICUS 2017 ; Conference date: 27-10-2017 Through 29-10-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/ICUS.2017.8278403",
language = "英语",
series = "Proceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "533--538",
editor = "Xin Xu",
booktitle = "Proceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017",
}