[1]TANG Kun,HAN Bin.A new fast algorithm of self-adaptive search scope for SIFT matching[J].CAAI Transactions on Intelligent Systems,2014,9(6):723-728.[doi:10.3969/j.issn.1673-4785.201309037]
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A new fast algorithm of self-adaptive search scope for SIFT matching
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
9
Number of periods:
2014 6
Page number:
723-728
Column:
学术论文—机器学习
Public date:
2014-12-25
- Title:
- A new fast algorithm of self-adaptive search scope for SIFT matching
- Keywords:
- SIFT; Auto ARV&; DP; feature points matching; search scope; BBF
- CLC:
- TP319
- DOI:
- 10.3969/j.issn.1673-4785.201309037
- Abstract:
- Aiming at the high time cost of feature vectors matching in scale invariant feature transform(SIFT), a fast algorithm, called auto angle of reference vector & distance of point(Auto ARV&DP), of self-adaptive search scope for SIFT matching is put forward. Firstly, an appropriate reference vector is computed based on the feature vectors set. Secondly, a self-adaptive search scope is determined by this reference vector. Finally, the matching of SIFT is performed in a small feature vectors set, which is filtered by Norm. Experimental results showed that compared with the classical best bin first(BBF) algorithm, Auto ARV&DP can effectively decrease the time cost of feature vector matching of SIFT with no loss of matching performance when the size of feature vector set is large.
- References:
-
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Last Update:
2015-06-16