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Stable detection of expanded target by the use of boosting random ferns
Deng, Li1,2,3; Wang, Chunhong1,2; Rao, Changhui1,2; Deng, L.
Volume8420
Pages84200A
2012
Language英语
ISSN0277786X
DOI10.1117/12.977284
Indexed ByEi
Subtype会议论文
AbstractThis paper studies the problem of keypoints recognition of extended target which lacks of texture information, and introduces an approach of stable detection of these targets called boosting random ferns (BRF). As common descriptors in this circumstance do not work as well as usual cases, matching of keypoints is hence turned into classification task so as to make use of the trainable characteristic of classifier. The kernel of BRF is consisted of random ferns as the classifier and AdaBoost (Adaptive Boosting) as the frame so that accuracy of random ferns classifier can be boosted to a relatively high level. Experiments compare BRF with widely used SURF descriptor and single random ferns classifier. The result shows that BRF obtains higher recognition rate of keypoints. Besides, for image sequence, BRF provides stronger stability than SURF in target detection, which proves the efficiency of BRF aiming to extended target which lacks of texture information. © 2012 SPIE.; This paper studies the problem of keypoints recognition of extended target which lacks of texture information, and introduces an approach of stable detection of these targets called boosting random ferns (BRF). As common descriptors in this circumstance do not work as well as usual cases, matching of keypoints is hence turned into classification task so as to make use of the trainable characteristic of classifier. The kernel of BRF is consisted of random ferns as the classifier and AdaBoost (Adaptive Boosting) as the frame so that accuracy of random ferns classifier can be boosted to a relatively high level. Experiments compare BRF with widely used SURF descriptor and single random ferns classifier. The result shows that BRF obtains higher recognition rate of keypoints. Besides, for image sequence, BRF provides stronger stability than SURF in target detection, which proves the efficiency of BRF aiming to extended target which lacks of texture information. © 2012 SPIE.
Conference NameProceedings of SPIE: 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical System Technologies for Manufacturing and Testing
Conference Date2012
Citation statistics
Document Type会议论文
Identifierhttp://ir.ioe.ac.cn/handle/181551/7782
Collection自适应光学技术研究室(八室)
Corresponding AuthorDeng, L.
Affiliation1. Laboratory on Adaptive Optics, Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, Sichuan 610209, China
2. Key Laboratory on Adaptive Optics, Chinese Academy of Sciences, Chengdu, Sichuan 610209, China
3. Graduate University, Chinese Academy of Sciences, Beijing 100039, China
Recommended Citation
GB/T 7714
Deng, Li,Wang, Chunhong,Rao, Changhui,et al. Stable detection of expanded target by the use of boosting random ferns[C],2012:84200A.
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