DocumentCode :
1795405
Title :
Rotation and affine-invariant SIFT descriptor for matching UAV images with satellite images
Author :
Mingguo Zheng ; Chengdong Wu ; Dongyue Chen ; Zhexiu Meng
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear :
2014
fDate :
8-10 Aug. 2014
Firstpage :
2624
Lastpage :
2628
Abstract :
Image matching is a key issue in Vision-Based UAV navigation problems. This paper presents an affine and rotation-invariant SIFT features descriptor for matching UAV image with satellite images. The SIFT and ASIFT algorithm are nowadays widely applied for robust image matching, but it also has a high computational complexity. SURF is used for real-time UAV position estimation but is not satisfied for affine invariant. We introduce the new SIFT feature descriptor based on pie chart region. This descriptor is invariant for rotation, affine, scale and the dimension of the feature vector is relatively reduced. Therefore, this method satisfies robustness and low computational complexity. Experiments show that this method can improve the matching accuracy and robustness.
Keywords :
autonomous aerial vehicles; computer vision; image matching; transforms; ASIFT algorithm; SURF; UAV image matching; affine-invariant SIFT feature descriptor; pie chart region; real-time UAV position estimation; rotation-invariant SIFT features descriptor; satellite images; unmanned aerial vehicle; vision-based UAV navigation problems; Educational institutions; Image matching; Satellite navigation systems; Satellites; Shape; Transforms; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4799-4700-3
Type :
conf
DOI :
10.1109/CGNCC.2014.7007582
Filename :
7007582
Link To Document :
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