A Linear Extrinsic Calibration of Kaleidoscopic Imaging System from Single 3D Point
This provides a more efficient calibration solution for researchers and practitioners in computer vision and imaging, though it is incremental as it builds on existing calibration techniques.
The paper tackles the problem of extrinsic calibration for kaleidoscopic imaging systems by estimating mirror normals and distances from a single 3D point, achieving this through a linear estimation method that outperforms conventional approaches in evaluations.
This paper proposes a new extrinsic calibration of kaleidoscopic imaging system by estimating normals and distances of the mirrors. The problem to be solved in this paper is a simultaneous estimation of all mirror parameters consistent throughout multiple reflections. Unlike conventional methods utilizing a pair of direct and mirrored images of a reference 3D object to estimate the parameters on a per-mirror basis, our method renders the simultaneous estimation problem into solving a linear set of equations. The key contribution of this paper is to introduce a linear estimation of multiple mirror parameters from kaleidoscopic 2D projections of a single 3D point of unknown geometry. Evaluations with synthesized and real images demonstrate the performance of the proposed algorithm in comparison with conventional methods.