基于OFern与PTAM算法的移动增强现实技术研究

当前，移动增强现实技术已成为虚拟现实领域的一个研究热点。由于移动设备内存较小且摄像头的采集范围有限，所以传统的增强现实算法难以满足移动用户的增强现实需求。为解决此类问题，本文提出一种基于OFern和PTAM算法相结合的增强现实技术，使其在较小的内存空间中就可以运行，且能实现较远距离的mark识别。实验证明，在满足较高的实时性和稳定性的同时，OFern算法得到的分类器尺寸减小到原始算法的1/8至1/10倍。融合PTAM算法后，在体验距离上较原始算法提高了13倍以上。

Mobile augmented reality technology research based on OFern and PTAM

At present, mobile augmented reality technology has become a research hotspot in the field of virtual reality. Due to the mobile device to smaller memory and camera collection scope is limited, So the traditional algorithm of augmented reality is difficult to meet the demand of mobile users of augmented reality. To solve such problems, this paper proposes a based on OFern and PTAM algorithm with the combination of augmented reality, make it can run in the smaller memory space, and can realize the long-distance mark recognition. Experiments show that in meet the real-time and stability at the same time, the higher OFern algorithm to get the size of the classifier to 1/8 to 1/10 times the size of the original algorithm. After fusion PTAM algorithm, on the experience of distance from the original algorithm is improved by more than 13 times.