Semi-independent Stereo Visual Odometry for Different Field of View Cameras

Trong Phuc Truong (1) , Vincent Nozick (2, 3) , Hideo Saito (1)

1 hvrl - hyper vision research lab
2 LIGM - Laboratoire d'Informatique Gaspard-Monge
3 JFLI - Japanese French Laboratory for Informatics

This paper presents a pipeline for stereo visual odometry using cameras with different fields of view. It gives a proof of concept about how a constraint on the respective field of view of each camera can lead to both an accurate 3D reconstruction and a robust pose estimation. Indeed, when considering a fixed resolution, a narrow field of view has a higher angular resolution and can preserve image texture details. On the other hand, a wide field of view allows to track features over longer periods since the overlap between two successive frames is more substantial. We propose a semi-independent stereo system where each camera performs individually temporal multi-view optimization but their initial parameters are still jointly optimized in an iterative framework. Furthermore , the concept of lead and follow camera is introduced to adaptively propagate information between the cameras. We evaluate the method qualitatively on two indoor datasets, and quantitatively on a synthetic dataset to allow the comparison across different fields of view.

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Traitement des images [eess.IV]

Trong Phuc Truong, Vincent Nozick, Hideo Saito. Semi-independent Stereo Visual Odometry for Different Field of View Cameras. 3D Reconstruction in the Wild (3DRW2018), Sep 2018, Munich, Germany. ⟨hal-01912878⟩