CASIA OpenIR
A Hardware-Oriented Algorithm for Ultra-High-Speed Object Detection
Li, Jianquan1,2; Liu, Xilong1,2; Liu, Fangfang1,2; Xu, De1,2; Gu, Qingyi1,2; Ishii, Idaku3
Source PublicationIEEE SENSORS JOURNAL
ISSN1530-437X
2019-05-15
Volume19Issue:10Pages:3818-3831
Corresponding AuthorGu, Qingyi(qingyi.gu@ia.ac.cn)
AbstractThis paper describes a novel hardware-oriented algorithm that can be implemented on a field-programmable gate array in a high-speed vision platform for detection of multiple objects with clear texture information in images of 512 x 512 pixels at 10000 frames per second (fps) under complex background. The proposed algorithm is specially designed for devices with limited hardware resource for high-frame-rate, high-data-throughput, and high-parallelism processing of video streams with low latency. The proposed algorithm is based on the conventional histograms of oriented gradient (HOC) descriptor and support vector machine classifier algorithms. Considering the trade-off between speed and accuracy, many hardware-based optimization operations were implemented. The data throughput is nearly 29.30 Gbps while the latency for feature extraction is 0.76 us (61 clock period). After hardware-based image processing, the source image and the detected object features can be transferred to a personal computer for recording or post-processing at 10000 fps. Several experiments were done to demonstrate the performance of our proposed algorithm for ultra-high-speed moving object detection with clear texture information in images.
KeywordHardware implementation high-frame-rate vision field-programmable gate array multi-object detection histograms of oriented gradient support vector machine
DOI10.1109/JSEN.2019.2895294
WOS KeywordFEATURES
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61673376] ; National Natural Science Foundation of China[61503376] ; Emergency Management Project of the National Natural Science Foundation of China[61741317]
Funding OrganizationNational Natural Science Foundation of China ; Emergency Management Project of the National Natural Science Foundation of China
WOS Research AreaEngineering ; Instruments & Instrumentation ; Physics
WOS SubjectEngineering, Electrical & Electronic ; Instruments & Instrumentation ; Physics, Applied
WOS IDWOS:000465288100029
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/24923
Collection中国科学院自动化研究所
Corresponding AuthorGu, Qingyi
Affiliation1.Chinese Acad Sci, Res Ctr Precis Sensing & Control, Inst Automat, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 101408, Peoples R China
3.Hiroshima Univ, Dept Syst Cybernet, Robot Lab, Hiroshima 7398527, Japan
First Author AffilicationChinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Li, Jianquan,Liu, Xilong,Liu, Fangfang,et al. A Hardware-Oriented Algorithm for Ultra-High-Speed Object Detection[J]. IEEE SENSORS JOURNAL,2019,19(10):3818-3831.
APA Li, Jianquan,Liu, Xilong,Liu, Fangfang,Xu, De,Gu, Qingyi,&Ishii, Idaku.(2019).A Hardware-Oriented Algorithm for Ultra-High-Speed Object Detection.IEEE SENSORS JOURNAL,19(10),3818-3831.
MLA Li, Jianquan,et al."A Hardware-Oriented Algorithm for Ultra-High-Speed Object Detection".IEEE SENSORS JOURNAL 19.10(2019):3818-3831.
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