转自：https://blog.csdn.net/qq_33591712/article/details/83050019

在做视觉里程计时，之间套用高博slam14讲的方法时报错：
OpenCV Error: Assertion failed ((type == CV_8U && dtype == CV_32S) || dtype == CV_32F) in batchDistance
原因：Since SIFT and SURF return a detectorType() of CV32F (=float) you cannot use any Hamming-distance as matcher. Hamming-distance works only for binary feature-types like ORB, FREAK, … I guess it would be possible if you’d convert them to CV8U. Afaik for SIFT this should be fairly easy since they are actually already normalized for the range 0-255 (double check that before you do it). However, I doubt that this is useful at all, use L2 norm for those and you should be fine.
orb描述子深度是CV_8U，可以用汉明距离的，而sift，surf，为CV32F直接套用汉明匹配则报错。

使用特征提取过程得到的特征描述符（descriptor）数据类型有的是float类型的，比如说SurfDescriptorExtractor，SiftDescriptorExtractor，有的是uchar类型的，比如说有ORB，BriefDescriptorExtractor。

对应float类型的匹配方式有：FlannBasedMatcher，BruteForce<L2>，BruteForce<SL2>，BruteForce<L1>。

对应uchar类型的匹配方式有：BruteForce，BruteForce。所以ORB和BRIEF特征描述子只能使用BruteForce匹配法。