Translation estimation for single viewpoint cameras using lines

Abstract

We present a translation estimation method for single viewpoint (SVP) cameras using line features. Images captured by multiple central cameras such as perspective, central catadioptric and fisheye cameras are mapped to spherical images using the unified projection model. It is possible to recover the camera rotations using vanishing points of parallel line sets. We then estimate the translations from known rotations and line images on the spheres. The algorithm has been validated on simulated data and real images. This vision-based estimation approach can be applied in navigation of autonomous robots besides the conventional devices such as Global Positioning System (GPS) and Inertial Navigation System (INS). It helps vision-based localization of a single robot or recovery of relative positions among multiple robots equipped with different types of cameras.