Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/42859
Título: Comparative performance of GPU, SIMD and OpenMP systems for raw template matching in computer vision
Autores/as: Mendez, Juan 
Lorenzo, Javier 
Castrillon, Modesto 
Clasificación UNESCO: 120304 Inteligencia artificial
Palabras clave: Computer Vision
Template Matching
Parallel Computing
GPU
Multi-Core Systems.
Fecha de publicación: 2011
Conferencia: 19th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 
19th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2011 
Resumen: Template matching is a traditional technique of Computer Vision whose advantages and disadvantages are known. However, advances in computer hardware allow computing it effectively with the use of SIMD instruction set, GPUs or multi-core systems. The computation of that low-level primitive in sub millisecond scale would improve high theoretical methods if they are used with high efficient primitives. This paper presents the comparative results of basic template matching by using SIMD instructions, multi-core systems and multi-GPU implementations. The results of this study will show that the high-specialized instruction in modern releases of SIMD and the use of multi-core systems outperforms the implementations based on GPUs for small mask size due to memory transfer cost. However, for big mask size GPU and SIMD systems have similar performance.
URI: http://hdl.handle.net/10553/42859
ISBN: 978-80-86943-83-1
Fuente: 19th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2011 - In Co-operation with EUROGRAPHICS, Full Papers Proceedings, p. 9-15
Colección:Actas de congresos
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