Plane registration leveraged by global constraints for context-aware AEC applications

In this article, we propose a new registration algorithm and computing framework, the KEG tracker, for estimating a camera's position and orientation for a general class of mobile context-aware applications in Architecture, Engineering, and Construction (AEC). By studying two classic natural marker-based registration algorithms, Homography-from-detection and Homography-from-tracking, and by overcoming their specific limitations of jitter and drift, our method applies two global constraints (geometric and appearance) to prevent tracking errors from propagating between consecutive frames. The proposed method is able to achieve an increase in both stability and accuracy, while being fast enough for real-time applications. Experiments on both synthesized and real-world test cases demonstrate that our method is superior to existing state-of-the-art registration algorithms. The article also explores several AEC applications of our method in context-aware computing and desktop-augmented reality.