期刊
IEEE ROBOTICS AND AUTOMATION LETTERS
卷 7, 期 4, 页码 11450-11457出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2022.3201253
关键词
SLAM; Localization; Computer Vision for Medical Robotics
类别
资金
- EU-H2020 through ENDOMAPPER [863146]
- Spanish Government [PGC2018-096367-B-I00, DPI2017-91104-EXP]
- MINECO [BES-2016-078678]
- Aragon Government [DGA_T45_20R]
Deformable Monocular SLAM algorithms recover the localization of a camera in an unknown deformable environment by using a local deformation model and a direct photometric error cost function, accurately identifying the deformation of the map.
Deformable Monocular SLAM algorithms recover the localization of a camera in an unknown deformable environment. Current approaches use a template-based deformable tracking to recover the camera pose and the deformation of the map. These template-based methods use an underlying global deformation model. In this letter, we introduce a novel deformable camera tracking method with a local deformation model for each point. Each map point is defined as a single textured surfel that moves independently of the other map points. Thanks to a direct photometric error cost function, we can track the position and orientation of the surfel without an explicit global deformation model. In our experiments, we validate the proposed system and observe that our local deformation model estimates more accurately the targeted deformations of the map in both laboratory-controlled experiments and in-body scenarios undergoing quasi-isometric deformations, with changing topology or discontinuities.
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