中文摘要：

提出一种基于向量夹角的近似最近邻搜索算法．该算法首先计算高维空间向量与随机选择的参考向量的夹角，并进行排序．计算出待查询向量与参考向量的夹角后，采用二分搜索算法在已排序夹角中查找对应的夹角，并以此夹角为中心，在一定范围内搜索给定向量的近似最近邻．实验结果表明，文中算法可显著提高尺度不变特征变换特征的匹配速度，并能获得满意的匹配效果．

英文摘要：

An approximate nearest neighbor search method based on vector angle is proposed. Firstly, the vector angles between high dimensional vectors and a stochastic selected reference vector are computed, and these angles are sorted. Then, the angle of reference vector and the query vector is computed, and the angle is found in the sorted angles by binary search algorithm. Finally, taking the angle as the center, the approximate nearest neighbor of the query vector is searched in the setting range. The experimental results show that the scale invariant feature transform feature matching can be accelerated significantly without underminin~ th,~ n,~,-~ t c__.