Egomotion Estimation Using Assorted Features
- Title
- Egomotion Estimation Using Assorted Features
- Author
- 임종우
- Keywords
- SLAM; Structure from motion; Tracking; Visual odometry
- Issue Date
- 2012-06
- Publisher
- Springer
- Citation
- Journal of Computer Vision, 2012, 98(2), P.202-216(15)
- Abstract
- We propose a novel minimal solver for recovering camera motion across two views of a calibrated stereo rig. The algorithm can handle any assorted combination of point and line features across the four images and facilitates a visual odometry pipeline that is enhanced by well-localized and reliably-tracked line features while retaining the well-known advantages of point features. The mathematical framework of our method is based on trifocal tensor geometry and a quaternion representation of rotation matrices. A simple polynomial system is developed from which camera motion parameters may be extracted more robustly in the presence of severe noise, as compared to the conventionally employed direct linear/subspace solutions. This is demonstrated with extensive experiments and comparisons against the 3-point and line-sfm algorithms.
- URI
- https://link.springer.com/article/10.1007%2Fs11263-011-0504-5http://hdl.handle.net/20.500.11754/67950
- ISSN
- 0920-5691
- DOI
- 10.1007/s11263-011-0504-5
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
- Files in This Item:
There are no files associated with this item.
- Export
- RIS (EndNote)
- XLS (Excel)
- XML