Fast k Nearest Neighbor Search using GPU
| dc.creator | Garcia, Vincent | |
| dc.creator | Debreuve, Eric | |
| dc.creator | Barlaud, Michel | |
| dc.date | 2008-04-09 | |
| dc.date.accessioned | 2026-07-07T09:31:18Z | |
| dc.date.available | 2026-07-07T09:31:18Z | |
| dc.description | The recent improvements of graphics processing units (GPU) offer to the computer vision community a powerful processing platform. Indeed, a lot of highly-parallelizable computer vision problems can be significantly accelerated using GPU architecture. Among these algorithms, the k nearest neighbor search (KNN) is a well-known problem linked with many applications such as classification, estimation of statistical properties, etc. The main drawback of this task lies in its computation burden, as it grows polynomially with the data size. In this paper, we show that the use of the NVIDIA CUDA API accelerates the search for the KNN up to a factor of 120. | |
| dc.description | 13 pages, 2figures, submitted to CVGPU 2008 | |
| dc.identifier | https://arxiv.org/abs/0804.1448 | |
| dc.identifier | http://arxiv.org/abs/0804.1448 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/158413 | |
| dc.subject | Computer Vision and Pattern Recognition | |
| dc.subject | Distributed, Parallel, and Cluster Computing | |
| dc.title | Fast k Nearest Neighbor Search using GPU | |
| dc.type | text |