The application of SIFT feature matching method in the aotomatic relative orientation;
由于使用了优化过程，该方法对相对定向参数的初值依赖性较小。
A fast and accurate image stitching algorithm based on SIFT feature matching is proposed.
基于SIFT特征匹配思想，提出一种快速、准确的图像拼接算法。
This paper presents a novel object tracking method based on SIFT(scale invariant feature transform) feature matching.
提出一种基于尺度不变特征变换（SIFT）特征匹配的目标跟踪方法。
And Scale Invariant Feature Transform (SIFT) was employed to exclude those sub-regions with smaller matching key points.
然后利用尺度不变特征变换(SIFT)剔除那些匹配的关键点数目少的子区域。
A simplified algorithm based on SIFT (SSIFT) is developed to express a feature point with only 12 dimensions based on a circular window to improve the efficiency of matching.
为了提高匹配速度，介绍了一种基于SIFT的简化算法(SSIFT)，采用基于圆形窗口的12维向量有效地表示一个特征点。
SIFT has proved to be the most robust local invariant feature descriptor in object recognition and matching.
目前，SIFT已经被证明鲁棒性最好的局部不变特征描述符。
SIFT has proved to be the most robust local invariant feature descriptor in object recognition and matching.
目前，SIFT已经被证明鲁棒性最好的局部不变特征描述符。
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