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Joint Rotation Invariant Feature for Vehicle Detection in Aerial Images
Li, Dawei; Li, Mingtao; Zheng, Jianhua; Wang, Yuanchao; Li, DW (reprint author), Chinese Acad Sci, Natl Space Sci Ctr, 1 Nanertiao, Beijing 100190, Peoples R China.; Li, DW (reprint author), Univ Chinese Acad Sci, 19 A Yuquan Rd, Beijing 100049, Peoples R China.
Department空间技术部
Source PublicationNINTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2017)
2017
Language英语
ISSN0277-786X
ISBN978-1-5106-1305-8; 978-1-5106-1304-1
AbstractThis paper introduces a joint feature of Fourier histograms of oriented gradients (FHOG) and local binary pattern (LBP) for vehicle detection in aerial images. Both of them are rotation invariant, so any rotation angle of vehicle in aerial images can be easily detected. A linear support vector machine (SVM) classifier is then trained over the joint feature vectors for the final vehicle detection. We evaluate our method on a public dataset and compare with some state-of-the-art algorithms, the proposed joint feature outperforms them in detecting small targets in complicated backgrounds.
Conference Name9th International Conference on Digital Image Processing (ICDIP)
Conference DateMAY 19-22, 2017
Conference PlaceHong Kong, PEOPLES R CHINA
Indexed ByEI ; CPCI
Document Type会议论文
Identifierhttp://ir.nssc.ac.cn/handle/122/6043
Collection空间技术部
Corresponding AuthorLi, DW (reprint author), Chinese Acad Sci, Natl Space Sci Ctr, 1 Nanertiao, Beijing 100190, Peoples R China.; Li, DW (reprint author), Univ Chinese Acad Sci, 19 A Yuquan Rd, Beijing 100049, Peoples R China.
Recommended Citation
GB/T 7714
Li, Dawei,Li, Mingtao,Zheng, Jianhua,et al. Joint Rotation Invariant Feature for Vehicle Detection in Aerial Images[C],2017.
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