DocumentCode :
1704632
Title :
SIFT and SURF feature analysis in visible and infrared imaging for UAVs
Author :
Xiaodong Li ; Aouf, Nabil
Author_Institution :
Dept. of Inf. & Syst. Eng., Cranfield Univ., Shrivenham, UK
fYear :
2012
Firstpage :
46
Lastpage :
51
Abstract :
This paper presents an in-depth analysis of the SIFT and SURF feature detection and matching techniques in characterizing natural environments for vision based navigation problems, in particular, the performance of feature extraction algorithms and matching when both visual and infrared data are used. With successful utilization of both feature extraction methods on different characteristic images, performance metrics include processing time, number of detected features and matching rate with RANSAC outlier rejection applied are discussed, with relevant conclusions made.
Keywords :
autonomous aerial vehicles; feature extraction; image matching; infrared imaging; mobile robots; object detection; path planning; robot vision; RANSAC outlier rejection; SIFT feature analysis; SURF feature analysis; UAV; characteristic images; feature detection; feature extraction algorithms; feature matching; infrared imaging; matching rate; processing time; random sample consensus; scale invariant feature transforms; speeded up robust features; unmanned aerial vehicles; visible imaging; vision based navigation problems; Computational modeling; Detectors; Feature extraction; Image sequences; Navigation; Robustness; Visualization; Features Extraction and Matching; RANSAC; SIFT; SURF; Visible and Infrared Image;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cybernetic Intelligent Systems (CIS), 2012 IEEE 11th International Conference on
Conference_Location :
Limerick
Type :
conf
DOI :
10.1109/CIS.2013.6782158
Filename :
6782158
Link To Document :
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