A Rapid and Efficient Feature Point Detection and Matching Algorithm

Xiao Ling Ding; Qiang Zhao; Yi Bin Li; Xin Ma

doi:10.4028/www.scientific.net/AMM.607.641

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 607A Rapid and Efficient Feature Point Detection and...

A Rapid and Efficient Feature Point Detection and Matching Algorithm

Abstract:

In the field of computer vision research, object feature detection and matching algorithm become a hot. Aiming at SIFT algorithm and SURF algorithm cannot meet the needs of real-time application, a feature point detection and matching algorithm based on orient FAST detector and rotation BRIEF descriptor is used. The experiments demonstrate that, this method not only remains the advantages of SURF but also improves the detection speed, and it can fully applicable to the field of computer vision to detect moving targets.

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Periodical:

Applied Mechanics and Materials (Volume 607)

Pages:

641-646

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.607.641

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Online since:

July 2014

Authors:

Xiao Ling Ding*, Qiang Zhao, Yi Bin Li, Xin Ma

Keywords:

Object Feature Detection, Orient FAST Detector, Rotation BRIEF Descriptor, SURF Algorithm

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References

[1] C．Harris and M．Stephens．A combined corner and edge detector [C]．In：Proceedings of the Alley Vision Conference，1988：147-151.

Google Scholar

[2] D．Lowe．Object recognition from local scale-invariant features[J]．Computer Vis- ion，1999，1(2)：1150-1157.

Google Scholar

[3] H．Bay，T．Tinne，and L．Van Gool．Surf：Speeded up robust features[C]．European Conference on Computer Vision，2006：404-417.

Google Scholar

[4] M．Calonder，V．Lepetit，C．Strecha，and P．Fua．Brief：Binary robust independent elementary features[C]．In European Conference on Computer Vision，2010：778-792.

Google Scholar

[5] E. Rosten and T．Drummond．Machine learning for highspeed corner detection[C]．In European Conference on Computer Vision，2006：430-443.

Google Scholar

[6] E．Rosten，R．Porter，and T．Drummond．Faster and better：A machine learning approach to corner detection[J]．IEEE Trans．Pattern Analysis and Machine Intelligence，2010：105–119.

Google Scholar

[7] P．L．Rosin．Measuring corner properties[J]．Computer Vision and Image Understanding，1999，73(2)：291–307.

Google Scholar

[8] M. Everingham. The PASCAL Visual Object Classes Challenge 2006 (VOC2006) Results. htt p: /pascallin. ecs. soton. ac. uk/challenges/VOC/databases. html.

Google Scholar

[9] E．Rublee，V．Rabaud，K．Konolige，and G．Bradski．ORB：an efficient alternative to SIFT or SURF[C]．In International Conference of Computer Vision(ICCV)，2011：2564-2571.

Google Scholar