Name
Abstract | ||
|---|---|---|
There has been growing interest in the use of binary-valued features, such as BRIEF, ORB, and BRISK for efficient local feature matching. These binary features have several advantages over vector-based features as they can be faster to compute, more compact to store, and more efficient to compare. Although it is fast to compute the Hamming distance between pairs of binary features, particularly on modern architectures, it can still be too slow to use linear search in the case of large datasets. For vector-based features, such as SIFT and SURF, the solution has been to use approximate nearest-neighbor search, but these existing algorithms are not suitable for binary features. In this paper we introduce a new algorithm for approximate matching of binary features, based on priority search of multiple hierarchical clustering trees. We compare this to existing alternatives, and show that it performs well for large datasets, both in terms of speed and memory efficiency. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CRV.2012.60 | CRV |
Keywords | Field | DocType |
vector-based feature,large datasets,pattern clustering,approximate matching,existing algorithm,image matching,brisk,binary feature,speed efficiency,trees (mathematics),nearest-neighbor search,binary features,efficient local feature matching,brief,surf,orb,hamming distance,nearest neighbors,memory efficiency,search problems,hierarchical clustering trees,vector-based features,priority search,feature matching,approximate nearest-neighbor search,local feature matching,fast matching,binary-valued features,sift,linear search,vectors,hierarchical clustering,nearest neighbor,clustering algorithms,feature extraction,nearest neighbor search,approximation algorithms | Hierarchical clustering,Approximation algorithm,Scale-invariant feature transform,Pattern recognition,Computer science,Feature extraction,Hamming distance,Artificial intelligence,Linear search,Cluster analysis,Nearest neighbor search | Conference |
ISBN | Citations | PageRank |
978-1-4673-1271-4 | 83 | 2.31 |
References | Authors | |
9 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marius Muja | 1 | 133 | 5.85 |
| D. G. Lowe | 2 | 15718 | 1413.60 |