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Robust Feature Matching Using The FESID Detector

Kerr, D, Coleman, SA and Scotney, BW (2011) Robust Feature Matching Using The FESID Detector. In: International Machine Vision and Image Processing Conference (IMVIP 2010), Limerick, Ireland. Cambridge Scholars Publishing, 12 Back Chapman Street, Newcastle upon Tyne, NE6 2XX, UK. 12 pp. [Conference contribution]


URL: http://www.c-s-p.org/flyers/14th-International-Machine-Vision-and-Image-Processing-Conference--IMVIP-20101-4438-2962-5.htm


Recently, interest point detectors and descriptors have become prominent in the field of computer vision and are typically used to determine correspondences between two images of the same scene. The finite element scale invariant detector (FESID) is based on a similar multi-scale approach to that used in the SURF detector. However, FESID detects point features rather than blob features, and by combining the derivative and smoothing operations into a single operator efficient performance is achieved. We illustrate the performance of the FESID algorithm with respect to both robustness and correct region matching.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
ID Code:20481
Deposited By: Dr Dermot Kerr
Deposited On:15 Nov 2011 11:08
Last Modified:09 Dec 2015 11:00

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