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An FPGA-Based Ultra-High-Speed Object Detection Algorithm with Multi-Frame Information Fusion

文献类型：期刊论文

作者Long, Xianlei1,2; Hu, Shenhua1,2; Hu, Yiming1,2; Gu, Qingyi1,2; Ishii, Idaku3
刊名SENSORS
出版日期2019-09-01
卷号19期号:17页码:16
关键词ultra-high-speed vision object detection field-programmable gate array histogram of oriented gradient multi-frame information fusion model
DOI10.3390/s19173707
通讯作者Gu, Qingyi(qingyi.gu@ia.ac.cn)
英文摘要An ultra-high-speed algorithm based on Histogram of Oriented Gradient (HOG) and Support Vector Machine (SVM) for hardware implementation at 10,000 frames per second (FPS) under complex backgrounds is proposed for object detection. The algorithm is implemented on the field-programmable gate array (FPGA) in the high-speed-vision platform, in which 64 pixels are input per clock cycle. The high pixel parallelism of the vision platform limits its performance, as it is difficult to reduce the strides between detection windows below 16 pixels, thus introduce non-negligible deviation of object detection. In addition, limited by the transmission bandwidth, only one frame in every four frames can be transmitted to PC for post-processing, that is, 75% image information is wasted. To overcome the mentioned problem, a multi-frame information fusion model is proposed in this paper. Image data and synchronization signals are first regenerated according to image frame numbers. The maximum HOG feature value and corresponding coordinates of each frame are stored in the bottom of the image with that of adjacent frames'. The compensated ones will be obtained through information fusion with the confidence of continuous frames. Several experiments are conducted to demonstrate the performance of the proposed algorithm. As the evaluation result shows, the deviation is reduced with our proposed method compared with the existing one.
资助项目National Natural Science Foundation of China[61673376]
WOS研究方向Chemistry ; Engineering ; Instruments & Instrumentation
语种英语
WOS记录号WOS:000486861900077
出版者MDPI
资助机构National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/26426]  
专题精密感知与控制研究中心_人工智能与机器学习
中国科学院自动化研究所
通讯作者Gu, Qingyi
作者单位1.Chinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 101408, Peoples R China
3.Hiroshima Univ, Dept Syst Cybernet, Robot Lab, Hiroshima 7398527, Japan
推荐引用方式
GB/T 7714		 Long, Xianlei,Hu, Shenhua,Hu, Yiming,et al. An FPGA-Based Ultra-High-Speed Object Detection Algorithm with Multi-Frame Information Fusion[J]. SENSORS,2019,19(17):16.
APA Long, Xianlei,Hu, Shenhua,Hu, Yiming,Gu, Qingyi,&Ishii, Idaku.(2019).An FPGA-Based Ultra-High-Speed Object Detection Algorithm with Multi-Frame Information Fusion.SENSORS,19(17),16.
MLA Long, Xianlei,et al."An FPGA-Based Ultra-High-Speed Object Detection Algorithm with Multi-Frame Information Fusion".SENSORS 19.17(2019):16.

入库方式： OAI收割

来源：自动化研究所

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