An innovative geometric pose reconstruction approach for marker-based single camera tracking

Mobile augmented reality applications are in need of tracking systems which can be wearable and do not cause high processing load, while still offering reasonable robustness, performance and accuracy. The motivation to develop yet another tracking algorithm is two-fold. Existing approaches use classical optimization techniques, which do not fully exploit the structure of the pose estimation problem with its geometric constraint targets. Also, mixed reality applications demand that pose estimation be not only accurate but also robust and computationally efficient. Hence there is a need for algorithms that are as accurate as classical algorithms, yet are also globally convergent and fast enough for real-time applications. In this paper we introduce a new iterative geometric method for pose estimation from four co-planar points and we present the current status of PTrack, an infrared marker-based single camera tracking system benefiting from this approach. Results show that our tracking system achieves competitive accuracy levels, while being highly stable and affordable.