# Revision history [back]

• In your case I'd rather use the BFMatcher, since you have a very small data. The speed-up you gain using LSH won't be huge!
• Flann with LSH is imho a good choice for matching many binary features.
• Afaik AutotundedIndexParams is not supported with LSH, so it would end up using a kd-tree or sth else.
• The building shouldn't be very time intensive for LSH, but you'd get an overhead here.
• Finding the correct parameters is always difficult, only try and error helps.
• No, these improvements are not included. However, they aren't included in the author's code either. So, you'd have to code them yourself. ALso note that OpenCV uses an older version, so if you really want to use it, I recommend to use the bug-fixed version of Muja (take care to get not confused with the different namespaces: cvflann::, cv::flann::, flann::).
• In your case I'd rather use the BFMatcher, since you have a deal w. very small data. The speed-up you gain using LSH won't be huge!huge and may be even neglected due to the creation of the index each time!
• Flann with LSH is imho a good choice for matching many binary features.
• Afaik AutotundedIndexParams is not supported with LSH, so it would end up using a kd-tree or sth else.
• The building shouldn't be very time intensive for LSH, but you'd get an overhead here.
• Finding the correct parameters is always difficult, only try and error helps.
• No, these improvements are not included. However, they aren't included in the author's code either. So, you'd have to code them yourself. ALso note that OpenCV uses an older version, so if you really want to use it, I recommend to use the bug-fixed version of Muja (take care to get not confused with the different namespaces: cvflann::, cv::flann::, flann::).
• In your case I'd rather use the BFMatcher, since you deal w. very small data. The speed-up you gain using LSH won't be huge and may be even neglected due to the creation of the index each time!
• Flann with LSH is imho a good choice for matching many binary features.
• Afaik AutotundedIndexParams is not supported with LSH, so it would end up using a kd-tree or sth else.
• The building shouldn't be very time intensive for LSH, but you'd get an overhead here.
• Finding the correct parameters is always difficult, only try and error helps.
• No, these improvements are not included. However, they aren't included in the author's code either. So, you'd have to code them yourself. ALso note . As @Nyenna pointed out, this feature is actually included in flann, called HierarchicalClusteringIndexParams() . Note that OpenCV uses an older version, so if you really want to use it, I recommend to use the bug-fixed version of Muja (take care to get not confused with the different namespaces: cvflann::, cv::flann::, flann::).