This project was part of my master thesis and was presented at Salento AVR 2014. We developed a novel optical tracking approach to accurately estimate the pose of a camera. 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.
Applications of the pattern include Augmented Reality and accurate camera calibration for multi-view setups where objects occlude parts of the pattern.