On Computing the Translations Norm in the Epipolar Graph
This work addresses a specific computational challenge in computer vision for camera geometry estimation, but it is incremental as it builds on existing epipolar graph methods.
The paper tackles the problem of recovering the unknown norm of relative translations between cameras using known relative rotations and translation directions, providing theoretical solvability conditions and a two-stage method that achieves accurate results in synthetic and real experiments.
This paper deals with the problem of recovering the unknown norm of relative translations between cameras based on the knowledge of relative rotations and translation directions. We provide theoretical conditions for the solvability of such a problem, and we propose a two-stage method to solve it. First, a cycle basis for the epipolar graph is computed, then all the scaling factors are recovered simultaneously by solving a homogeneous linear system. We demonstrate the accuracy of our solution by means of synthetic and real experiments.