Robust Global Tracking Using a Seamless Structured Pattern of Dots

Abstract

In this paper, we present a novel optical tracking approach to accurately estimate the pose of a camera in large scene augmented reality (AR). Traditionally, larger scenes are provided with multiple markers with their own identifier and coordinate system. However, when any part of a single marker is occluded, the marker cannot be identified. Our system uses a seamless structure of dots where the world position of each dot is represented by its spatial relation to neighboring dots. By using only the dots as features, our marker can be robustly identified. We use projective invariants to estimate the global position of the features and exploit temporal coherence using optical flow. With this design, our system is more robust against occlusions. It can also give the user more freedom of movement allowing them to explore objects up close and from a distance.