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标 题: Fast Scene Recognition and Camera Relocalisation for Wide Area Augmented Reality Systems
作 者: Guan tao,Duan liya, Chen yongjian
会议 / 期刊: Sensors,10(6):6017-6043(SCI收录)
发 表 时 间: 2010年
下 载 地 址: 点击下载
论文摘要
This paper focuses on online scene learning and fast camera relocalisation which are two key problems currently limiting the per
formance of wide area augmented reality systems.Firstly, we propose to use adaptive random trees to deal with the online scene
learning problem. The algorithm can provide more accurate recognition rates than traditional methods,especially with large scale
workspaces. Secondly, we use the enhanced PROSAC algorithm to obtain a fast camera relocalisation method.Compared with traditiona
l algorithms,our method can significantly reduce the computation complexity, which facilitates to a large degree the process of o
nline camera relocalisation.Finally, we implement our algorithms in a multithreaded manner by using a parallel-computing scheme.
Camera tracking,scene mapping,scene learning and relocalisation are separated into four threads by using multi-CPU hardware archi
tecture. While providing real-time tracking performance, the resulting system also possesses the ability to track multiple maps
simultaneously. Some experiments have been conducted to demonstrate the validity of our methods.

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