TY - GEN
T1 - Bundle adjustment without iterative structure estimation and its application to navigation
AU - Indelman, Vadim
PY - 2012
Y1 - 2012
N2 - This paper describes a new approach for bundle adjustment (BA), which is based on a non-linear optimization of only the camera pose for all the views in a given sequence of images and does not involve iterative structure estimation. If required, structure reconstruction can be performed based on the camera matrices after convergence of the optimization process. Instead of applying the projection equations, the cost function being optimized in the suggested approach is based on the three-view geometry constraints that should be satisfied for any three views with a common overlapping area. Significant reduction in computational complexity is obtained compared to a standard BA, since the number of unknown parameters participating in the iterative optimization is much smaller. The optimization problem is formulated relative to the camera pose of the first view, as commonly used in robotics navigation aplications. The proposed method is demonstrated on a publiclly available dataset of real images and the optimized camera pose and the recovered structure are compared to the ground truth.
AB - This paper describes a new approach for bundle adjustment (BA), which is based on a non-linear optimization of only the camera pose for all the views in a given sequence of images and does not involve iterative structure estimation. If required, structure reconstruction can be performed based on the camera matrices after convergence of the optimization process. Instead of applying the projection equations, the cost function being optimized in the suggested approach is based on the three-view geometry constraints that should be satisfied for any three views with a common overlapping area. Significant reduction in computational complexity is obtained compared to a standard BA, since the number of unknown parameters participating in the iterative optimization is much smaller. The optimization problem is formulated relative to the camera pose of the first view, as commonly used in robotics navigation aplications. The proposed method is demonstrated on a publiclly available dataset of real images and the optimized camera pose and the recovered structure are compared to the ground truth.
UR - http://www.scopus.com/inward/record.url?scp=84866235695&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/PLANS.2012.6236952
DO - https://doi.org/10.1109/PLANS.2012.6236952
M3 - منشور من مؤتمر
SN - 9781467303866
T3 - Record - IEEE PLANS, Position Location and Navigation Symposium
SP - 748
EP - 756
BT - Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium, PLANS 2012
T2 - 2012 IEEE/ION Position, Location and Navigation Symposium, PLANS 2012
Y2 - 23 April 2012 through 26 April 2012
ER -