The Orthographic Projection Model for Pose Calibration of Long Focal Images

Laura F Julià (1) , Pascal Monasse (1) , Marc Pierrot-Deseilligny (2)

1 LIGM - Laboratoire d'Informatique Gaspard-Monge
2 LaSTIG - Laboratoire des Sciences et Technologies de l'Information Géographique

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. Source Code The Matlab implementation of this algorithm is available in the IPOL web page of this article 1. Usage instructions are included in the README.txt file of the archive. Note that the input data are the image correspondences, so it might be necessary to launch an independent matching algorithm in a first step.

Mots clés: pose estimation; calibration; camera model

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Laura F Julià, Pascal Monasse, Marc Pierrot-Deseilligny. The Orthographic Projection Model for Pose Calibration of Long Focal Images. Image Processing On Line, 2019, 9, pp.231-250. ⟨10.5201/ipol.2019.248⟩. ⟨hal-02284935⟩