We address the model-to-image registration problem with line features in the following two ways. (a) We present a robust solution to simultaneously recover the camera pose and the three-dimensional-to-two-dimensional line correspondences. With weak pose priors, our approach progressively verifies the pose guesses with a Kalman filter by using a subset of recursively found match hypotheses. Experiments show our method is robust to occlusions and clutter. (b) We propose a new line feature based pose estimation algorithm, which iteratively optimizes the objective function in the object space. Experiments show that the algorithm has strong robustness to noise and outliers and that it can attain very accurate results efficiently.
© 2012 Optical Society of America
Original Manuscript: October 17, 2011
Revised Manuscript: December 7, 2011
Manuscript Accepted: December 17, 2011
Published: February 28, 2012
Xiaohu Zhang, Zheng Zhang, You Li, Xianwei Zhu, Qifeng Yu, and Jianliang Ou, "Robust camera pose estimation from unknown or known line correspondences," Appl. Opt. 51, 936-948 (2012)