A novel method for camera pose tracking using visual complementary filtering

Abstract

Camera pose tracking is one of the major problems of Augmented Reality (AR) system. While tracking technologies based on fiducial markers have dominated the development of AR applications for almost a decade, various real-time approaches to Natural-Image-Marker tracking have recently been presented. However, most existing approaches do not yet achieve sufficient frame rates for AR on mobile phones or at least require an extensive training phase in advance. In this paper, we propose a novel method for fast camera pose tracking using visual complementary filtering. Compared with existing methods, our method improves the accuracy at the same time guarantee the running speed. Our method can be used in Augmented Reality System with a stored natural image. The implementation is very fast and robust, allowing running even on mobile phones at highly interactive rates and accuracy. Our implementation can immediately track features captured from a photo without any training. © Springer International Publishing AG, part of Springer Nature 2018.