DocumentCode :
3672257
Title :
Real-time joint estimation of camera orientation and vanishing points
Author :
Jeong-Kyun Lee; Kuk-Jin Yoon
Author_Institution :
Computer Vision Laboratory, Gwangju Institute of Science and Technology, Korea
fYear :
2015
fDate :
6/1/2015 12:00:00 AM
Firstpage :
1866
Lastpage :
1874
Abstract :
A widely-used approach for estimating camera orientation is to use points at infinity, i.e., vanishing points (VPs). By enforcing the orthogonal constraint between the VPs, called the Manhattan world constraint, a drift-free camera orientation estimation can be achieved. However, in practical applications this approach suffers from many spurious parallel line segments or does not perform in non-Manhattan world scenes. To overcome these limitations, we propose a novel method that jointly estimates the VPs and camera orientation based on sequential Bayesian filtering. The proposed method does not require the Manhattan world assumption, and can perform a highly accurate estimation of camera orientation in real time. In addition, in order to enhance the robustness of the joint estimation, we propose a feature management technique that removes false positives of line clusters and classifies newly detected lines. We demonstrate the superiority of the proposed method through an extensive evaluation using synthetic and real datasets and comparison with other state-of-the-art methods.
Keywords :
"Cameras","Estimation","Three-dimensional displays","Image segmentation","Robustness","Joints","Feature extraction"
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on
Electronic_ISBN :
1063-6919
Type :
conf
DOI :
10.1109/CVPR.2015.7298796
Filename :
7298796
Link To Document :
بازگشت