A Framework for Augmented Reality using Non-Central Catadioptric Cameras

Abstract

This paper addresses the problem of augmented reality on images acquired from non-central catadioptric systems. We propose a solution which allows the projection of textured objects to images of these type of systems and, depending on the complexity of the objects, can run up to 20 fps, using a 1328 × 1048 image resolution. The main contributions are related with the image formation of the non-central catadioptric cameras: projection of the 3D segments onto the image of non-central catadioptric cameras; occlusions; and illumination/shading. To validate the proposed solution, we used a non-central catadioptric camera formed with a perspective camera and a spherical mirror. Also, to test the robustness of the proposed method, we used a regular object (a parallelepiped) and three well known irregular objects Electronic supplementary material The online version of this article (

Pose Estimation of Omnidirectional Camera with Improved EPnP Algorithm

“…Recently, omnidirectional vision system has become a hot topic for researchers in some fields such as robot driving [6,7], augmented reality [8], and video surveillance [9][10][11]. An omnidirectional vision system provides a 360-degree panorama in the horizontal direction and is composed of a common CCD and mirror.…”