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CORR
2008
Springer

Fast k Nearest Neighbor Search using GPU

13 years 11 months ago
Fast k Nearest Neighbor Search using GPU
Statistical measures coming from information theory represent interesting bases for image and video processing tasks such as image retrieval and video object tracking. For example, let us mention the entropy and the Kullback-Leibler divergence. Accurate estimation of these measures requires to adapt to the local sample density, especially if the data are high-dimensional. The k nearest neighbor (kNN) framework has been used to define efficient variable-bandwidth kernel-based estimators with such a locally adaptive property. Unfortunately, these estimators are computationally intensive since they rely on searching neighbors among large sets of d-dimensional vectors. This computational burden can be reduced by pre-structuring the data, e.g. using binary trees as proposed by the Approximated Nearest Neighbor (ANN) library. Yet, the recent opening of Graphics Processing Units (GPU) to generalpurpose computation by means of the NVIDIA CUDA API offers the image and video processing communit...
Vincent Garcia, Eric Debreuve, Michel Barlaud
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2008
Where CORR
Authors Vincent Garcia, Eric Debreuve, Michel Barlaud
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