PUMA
Istituto di Informatica e Telematica     
Hast A., Marchetti A. The Challenges and Advantages with a Parallel Implementation of Feature Matching. In: 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (Roma, Italy, 2016-02-27).
 
 
Abstract
(English)
The number of cores per cpu is predicted to double every second year. Therefore, the opportunity to parallelise currently used algorithms in computer vision and image processing needs to be addressed sooner rather than later. A parallel feature matching approach is proposed and evaluated in Matlab. The key idea is to use different interest point detectors so that each core can work on its own subset independently of the others. However, since the image pairs are the same, the homography will be essentially the same and can therefore be distributed by the process that first finds a solution. Nevertheless, the speedup is not linear and reasons why is discussed.
Abstract
(Italiano)
The number of cores per cpu is predicted to double every second year. Therefore, the opportunity to parallelise currently used algorithms in computer vision and image processing needs to be addressed sooner rather than later. A parallel feature matching approach is proposed and evaluated in Matlab. The key idea is to use different interest point detectors so that each core can work on its own subset independently of the others. However, since the image pairs are the same, the homography will be essentially the same and can therefore be distributed by the process that first finds a solution. Nevertheless, the speedup is not linear and reasons why is discussed.
URL: http://dx.doi.org/10.5220/0005674501010106
DOI: 10.5220/0005674501010106
Subject Parallel Implementation
Interest Points
RANSAC
Feature Matching
I.4 IMAGE PROCESSING AND COMPUTER VISION


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