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 reg- istration 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 con- secutive 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 com- puting and desktop-augmented reality.