Augmented reality registration algorithm based on nature feature recognition

This paper presents an improved key frame based augmented reality registration algorithm for real-time motion tracking in outdoor environment. In such applications, wide-baseline feature matching is a critical problem. In this paper, we apply randomized tree method to match key points extracted from the input image to those key frames as a classification problem. Extended Kalman filter is also utilized for jitter correction. A video see-through mobile augmented reality system is built for the on-site digital reconstruction of Yuanmingyuan Garden. Experimental results demonstrate that this algorithm is real-time, robust and effective for outdoor tracking.