- published
- 2019-09-05
- reference
- Laura F. Julià, Pascal Monasse, and Marc Pierrot-Deseilligny, The Orthographic Projection Model for Pose Calibration of Long Focal Images, Image Processing On Line, 9 (2019), pp. 231–250. https://doi.org/10.5201/ipol.2019.248
Communicated by Gabriele Facciolo
Demo edited by Pascal Monasse
Abstract
Most stereovision and Structure from Motion (SfM) methods rely on the pinhole camera model based on perspective projection. From this hypothesis the fundamental matrix and the epipolar constraints are derived, which are the milestones of pose estimation. In this article we present a method based on the matrix factorization due to Tomasi and Kanade that relies on a simpler camera model, resulting in orthographic projection. This method can be used for the pose estimation of perspective cameras in configurations where other methods fail, in particular, when using cameras with long focal length lenses. We show this projection is an approximation of the pinhole camera model when the camera is far away from the scene. The performance of our implementation of this pose estimation method is compared to that given by the perspective-based methods for several configurations using both synthetic and real data. We show through some examples and experiments that the accuracy achieved and the robustness of this method make it worth considering in any SfM procedure.
Download
- full text manuscript: PDF (4.4MB)
- source code: TAR/GZ
History
- the manuscript of the article was modified on 2022-01-01 to include information about its editors. The original version of the manuscript is available here.
- the code of the article was modified on 2024-01-21 to fix a bug that occurred when too few matching points were found. The original version of the code is available here.
- the code of the article was modified on 2024-01-25 to fix a bug that occurred when too few matching points were found. The original version of the code is available here.