Augmented reality registration algorithm based on nature feature recognition

• Published in: Science China. Information sciences Vol. 53; no. 8; pp. 1555 - 1565
• Main Authors: Chen, Jing, Wang, YongTian, Guo, JunWei, Liu, Wei, Lin, JingDun, Xue, Kang, Liu, Yue, Ding, GangYi
• Format: Journal Article
• Language: English
• Published: Heidelberg SP Science China Press 01.08.2010; Springer Nature B.V
• Subjects: Algorithms; Augmented reality; China; Classification; Computer Science; Extended Kalman filter; Feature recognition; Frames; Information Systems and Communication Service; Outdoor; Real time; Research Papers; Tracking; 增强现实系统; 实时跟踪; 户外环境; 扩展卡尔曼滤波器; 注册算法; 特征匹配; 特征识别; camera tracking; randomized tree; outdoor augmented reality
• ISSN: 1674-733X; 1869-1919
• DOI: 10.1007/s11432-010-4026-5

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.