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Augmented reality registration algorithm based on nature feature recognition
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DOI：10.1007/s11432-010-4026-5.png)
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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.
Keyword:
outdoor augmented reality
camera tracking
randomized tree
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