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Fast aircraft detection using cascaded discriminative model in photoelectric sensing system
Zhong, Jiandan1,2; Lei, Tao; Yao, Guangle1,2; Tang, Zili3; Liu, Yinhui1,2
Source PublicationOPTICAL REVIEW
Volume24Issue:3Pages:383-397
2017
Language英语
ISSN1340-6000
Indexed BySCI
AbstractAircraft detection is a fundamental problem in computer vision. As a vision-based system, the photoelectric sensing system (in airport) needs to capture the aircrafts quickly and accurately by the optical camera. Although many existing detection models reach to favorable accuracy, they are time consuming in training and testing, which is not suitable for this system. In practice, as a core part of vision-based system, detection module always occupies a lot of time in image processing and target matching. To reduce the (detection) time cost without losing detection accuracy, we designed a cascade discriminative model which includes two stages: coarse pre-detection stage and fine detection stage. In the traditional object detection models, generally, an object feature template was employed to search for all positions and levels in image pyramid with sliding window fashion. However, in our detection model, only a small number of candidate regions were pre-detected to reduce the searching space at the first stage. At the second stage, an assembled method (which includes partitioned bag-of-words method and random forest) was adopted for accelerating the feature quantization and formation. Then, the possible regions including object were decided by a non-linear SVM classifier. We evaluated our model on two benchmark databases (Caltech 101 and PASCAL 2007) and our own database (images were obtained from the optical camera), and it yields high performance. Compared with other state-of- the-art methods, our model outperforms them not only in detection speed, but also in detection accuracy.
KeywordAircraft detection Objectness Bag-of-words Random forest
Document Type期刊论文
Identifierhttp://ir.ioe.ac.cn/handle/181551/8854
Collection光电测控技术研究室(三室)
Affiliation1.Chinese Acad Sci, Inst Opt & Elect, POB 350, Chengdu 610209, Sichuan, Peoples R China
2.Univ Elect Sci & Technol China, 4,Sect 2,North Jianshe Rd, Chengdu 610054, Sichuan, Peoples R China
3.Univ Chinese Acad Sci, 19 A Yuquan Rd, Beijing 100039, Peoples R China
4.China Huayin Ordnance Test Ctr, Huayin 714200, Peoples R China
Recommended Citation
GB/T 7714
Zhong, Jiandan,Lei, Tao,Yao, Guangle,et al. Fast aircraft detection using cascaded discriminative model in photoelectric sensing system[J]. OPTICAL REVIEW,2017,24(3):383-397.
APA Zhong, Jiandan,Lei, Tao,Yao, Guangle,Tang, Zili,&Liu, Yinhui.(2017).Fast aircraft detection using cascaded discriminative model in photoelectric sensing system.OPTICAL REVIEW,24(3),383-397.
MLA Zhong, Jiandan,et al."Fast aircraft detection using cascaded discriminative model in photoelectric sensing system".OPTICAL REVIEW 24.3(2017):383-397.
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