Camera Orientation Estimation Using Motion-Based Vanishing Point Detection for Advanced Driver-Assistance Systems
- Authors
- Jang, Jinbeum; Jo, Youngran; Shin, Minwoo; Paik, Joonki
- Issue Date
- Oct-2021
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Cameras; Calibration; Estimation; Roads; Three-dimensional displays; Feature extraction; Computer vision; Extrinsic calibration; camera orientation estimation; motion vector; 3-line RANSAC
- Citation
- IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, v.22, no.10, pp 6286 - 6296
- Pages
- 11
- Journal Title
- IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Volume
- 22
- Number
- 10
- Start Page
- 6286
- End Page
- 6296
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/50503
- DOI
- 10.1109/TITS.2020.2990983
- ISSN
- 1524-9050
1558-0016
- Abstract
- Advanced driver-assistance systems need a camera calibration algorithm for various vision applications including surround-view monitoring (SVM) and lane departure warning (LDW). Although cameras mounted on a vehicle are calibrated in the manufacturing process, their orientation angles are subject to tilting because of continuing vibration and external impact. To solve the problem, this paper presents an online calibration algorithm for camera orientation estimation using motion vectors and three-dimensional geometry. The proposed algorithm consists of three steps: i) driving direction estimation by calculating an intersection of motion vectors, ii) camera orientation estimation based on 3-line random sample consensus (RANSAC) using the estimated intersection, and iii) final orientation decision using extended Kalman filter from the result of each frame. Experimental results demonstrate that the proposed algorithm stably estimates camera orientation angles from motion vectors and lines under the parallelism and orthogonality assumptions.
- 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
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.