TY - GEN
T1 - Extrinsic camera calibration using multiple reflections
AU - Hesch, Joel A.
AU - Mourikis, Anastasios I.
AU - Roumeliotis, Stergios I.
PY - 2010
Y1 - 2010
N2 - This paper presents a method for determining the six-degree-of-freedom (DOF) transformation between a camera and a base frame of interest, while concurrently estimating the 3D base-frame coordinates of unknown point features in the scene. The camera observes the reflections of fiducial points, whose base-frame coordinates are known, and reconstruction points, whose base-frame coordinates are unknown. In this paper, we examine the case in which, due to visibility constraints, none of the points are directly viewed by the camera, but instead are seen via reflection in multiple planar mirrors. Exploiting these measurements, we analytically compute the camera-to-base transformation and the 3D base-frame coordinates of the unknown reconstruction points, without a priori knowledge of the mirror sizes, motions, or placements with respect to the camera. Subsequently, we refine the analytical solution using a maximum-likelihood estimator (MLE), to obtain high-accuracy estimates of the camera-to-base transformation, the mirror configurations for each image, and the 3D coordinates of the reconstruction points in the base frame. We validate the accuracy and correctness of our method with simulations and real-world experiments.
AB - This paper presents a method for determining the six-degree-of-freedom (DOF) transformation between a camera and a base frame of interest, while concurrently estimating the 3D base-frame coordinates of unknown point features in the scene. The camera observes the reflections of fiducial points, whose base-frame coordinates are known, and reconstruction points, whose base-frame coordinates are unknown. In this paper, we examine the case in which, due to visibility constraints, none of the points are directly viewed by the camera, but instead are seen via reflection in multiple planar mirrors. Exploiting these measurements, we analytically compute the camera-to-base transformation and the 3D base-frame coordinates of the unknown reconstruction points, without a priori knowledge of the mirror sizes, motions, or placements with respect to the camera. Subsequently, we refine the analytical solution using a maximum-likelihood estimator (MLE), to obtain high-accuracy estimates of the camera-to-base transformation, the mirror configurations for each image, and the 3D coordinates of the reconstruction points in the base frame. We validate the accuracy and correctness of our method with simulations and real-world experiments.
UR - http://www.scopus.com/inward/record.url?scp=78149334883&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78149334883&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15561-1_23
DO - 10.1007/978-3-642-15561-1_23
M3 - Conference contribution
AN - SCOPUS:78149334883
SN - 364215560X
SN - 9783642155604
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 311
EP - 325
BT - Computer Vision, ECCV 2010 - 11th European Conference on Computer Vision, Proceedings
PB - Springer Verlag
T2 - 11th European Conference on Computer Vision, ECCV 2010
Y2 - 10 September 2010 through 11 September 2010
ER -