| Title | Continuous-Time Stereo Visual Odometry Based on Dynamics Model |
| Authors | Wang, Xin Xue, Fei Yan, Zike Dong, Wei Wang, Qiuyuan Zha, Hongbin |
| Affiliation | Peking Univ, Sch EECS, Key Lab Machine Percept MOE, Beijing, Peoples R China Shanghai Jiao Tong Univ, Cooperat Medianet Innovat Ctr, Shanghai, Peoples R China Carnegie Mellon Univ, Inst Robot, Pittsburgh, PA 15213 USA |
| Issue Date | 2019 |
| Publisher | COMPUTER VISION - ACCV 2018, PT VI |
| Abstract | We propose a dynamics model to represent the camera trajectory as a continuous function of time and forces. Equipped with such a representation, we convert the classical visual odometry problem to analyzing the forces applied to the camera. In contrast to the classical discrete-time estimation strategy, the continuous nature of the camera motion is inherently revealed in the framework, and the camera motion can be simply modeled with only few parameters within time intervals. The dynamics model guarantees the continuous velocity, and hence assures a smooth trajectory, which is robust against noise and avoiding the pose vibration. Evaluations on real-world benchmark datasets show that our method outperforms other continuous-time methods. |
| URI | http://hdl.handle.net/20.500.11897/553077 |
| ISSN | 0302-9743 |
| DOI | 10.1007/978-3-030-20876-9_25 |
| Indexed | CPCI-S(ISTP) EI |
| Appears in Collections: | 信息科学技术学院 机器感知与智能教育部重点实验室 |
