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ICAPR
2009
Springer

Hierarchical Local Maps for Robust Approximate Nearest Neighbor Computation

10 years 8 months ago
Hierarchical Local Maps for Robust Approximate Nearest Neighbor Computation
In this paper, we propose a novel method for fast nearest neighbors retrieval in non-Euclidean and non-metric spaces. We organize the data into a hierarchical fashion that preserves the local similarity structure. A method to find the approximate nearest neighbor of a query is proposed, that drastically reduces the total number of explicit distance measures that need to be computed. The representation overcomes the restrictive assumptions in traditional manifold mappings, while enabling fast nearest neighbor’s search. Experimental results on the Unipen and CASIA Iris datasets clearly demonstrates the advantages of the approach and improvements over state of the art algorithms. The algorithm can work in batch mode as well as in sequential mode and is highly scalable.
Pratyush Bhatt, Anoop M. Namboodiri
Added 26 May 2010
Updated 26 May 2010
Type Conference
Year 2009
Where ICAPR
Authors Pratyush Bhatt, Anoop M. Namboodiri
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