14. K. Mikolajczyk: Efficient Clustering and Matching of Local Features
In this work we address the problem of building object class
representations
based on local features and fast matching in a large database.
We examine different agglomerative and partitional clustering strategies
and compare the quality of obtained clusters.
We also evaluate methods for building data structures and different
search strategies in high dimensional feature spaces.
In particular we compare the approaches proposed by Nister-CVPR06 and
Mikolajczyk-CVPR06.
These methods allow to deal with large sets of data typically used in
image retrieval and multiclass recognition.