Estimation of omnidirectional camera model with one parametric projection
- Authors
- Hwang, Y.; Hong, H.
- Issue Date
- 2006
- Citation
- Lecture Notes in Control and Information Sciences, v.345, pp 827 - 833
- Pages
- 7
- Journal Title
- Lecture Notes in Control and Information Sciences
- Volume
- 345
- Start Page
- 827
- End Page
- 833
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/65441
- DOI
- 10.1007/11816515_99
- ISSN
- 0170-8643
- Abstract
- This paper presents a new self-calibration algorithm of omnidirectional camera from uncalibrated images. First, one parametric non-linear projection model of omnidirectional camera is estimated with the known rotation and translation parameters. After deriving projection model, we can compute an essential matrix of unknown camera motions, and then determine the camera positions. In addition, we showed that LMS (Least-Median-Squares) is most suitable for inlier sampling in our model than other methods: 8-points algorithm and RANSAC (RANdom Sampling Consensus). In the simulation results, we demonstrated that the proposed algorithm can achieve a precise estimation of the omnidirectional model and extrinsic parameters. © Springer-Verlag Berlin/Heidelberg 2006.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/65441)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.