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| DOI | 10.1109/TCI.2016.2612942 | ||
| Año | 2017 | ||
| Tipo | artículo de investigación |
Citas Totales
Autores Afiliación Chile
Instituciones Chile
% Participación
Internacional
Autores
Afiliación Extranjera
Instituciones
Extranjeras
We present an efficient and flexible GPU implementation of a highly-parallelizable and scalable image formation pipeline for gigapixel images based on the MapReduce framework. The presented implementation was developed to operate with the AWARE multiscale gigapixel cameras, but it is also able to efficiently form gigapixel images from any source. The AWARE cameras are compact camera arrays that simultaneously collect images that span a wide field-of-view to generate high-resolution and high dynamic range panoramic images and video. The proposed GPU implementation exploits the mutiscale nature of the AWARE image acquisition, not only enabling the fast composition of gigapixel-scale panoramas, but also the rapid formation of images of arbitrary portions of the field-of-view at current display-scale resolutions at video rates.
| Ord. | Autor | Género | Institución - País |
|---|---|---|---|
| 1 | Gong, Qian | - |
Duke Univ - Estados Unidos
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| 2 | Vera, Esteban | Hombre |
Pontificia Universidad Católica de Valparaíso - Chile
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| 3 | Golish, Dathon R. | - |
UNIV ARIZONA - Estados Unidos
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| 4 | Feller, Steven D. | Hombre |
Aqueti Inc - Estados Unidos
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| 5 | Brady, David J. | Hombre |
Duke Univ - Estados Unidos
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| 6 | Gehm, Michael E. | Hombre |
Duke Univ - Estados Unidos
|