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应用于嵌入式图形处理器的实时目标检测方法

Real-Time Target Detection Method Applied to Embedded Graphic Processing Unit

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摘要

提出了一种应用于嵌入式图形处理器(GPU)的实时目标检测算法。针对嵌入式平台计算单元较少、处理速度较慢的现状,提出了一种基于YOLO-V3(You Only Look Once-Version 3)架构的改进的轻量目标检测模型,对汽车目标进行了离线训练,在嵌入式平台上部署训练好的模型,实现了在线检测。实验结果表明,在嵌入式平台上,所提方法对分辨率为640 pixel×480 pixel的视频图像的检测速度大于23 frame/s。

Abstract

A real-time target detection algorithm is proposed and used in the embedded graphic processing unit (GPU). In view of the lack of computing units and the slow processing speed for an embedded platform, an improved lightweight target detection model is proposed based on the YOLO-V3 (You Only Look Once-Version 3) structure. This model is first trained off-line with vehicle targets and then deployed on the embedded GPU platform to achieve the online prediction. The experimental results show that the processing speed of the proposed method on the embedded GPU platform reaches 23 frame/s for a 640 pixel×480 pixel video.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:TP317.4

DOI:10.3788/AOS201939.0315005

所属栏目:机器视觉

基金项目:国家自然科学基金面上项目(51575388)

收稿日期:2018-09-07

修改稿日期:2018-10-22

网络出版日期:2018-11-08

作者单位    点击查看

王晓青:天津大学精密测试技术及仪器国家重点实验室, 天津 300072
王向军:天津大学精密测试技术及仪器国家重点实验室, 天津 300072

联系人作者:王向军(tjuxjw@126.com)

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引用该论文

Wang Xiaoqing,Wang Xiangjun. Real-Time Target Detection Method Applied to Embedded Graphic Processing Unit[J]. Acta Optica Sinica, 2019, 39(3): 0315005

王晓青,王向军. 应用于嵌入式图形处理器的实时目标检测方法[J]. 光学学报, 2019, 39(3): 0315005

被引情况

【1】刘万军,王凤,曲海成. 融合多尺度特征的目标检测模型. 激光与光电子学进展, 2019, 56(23): 231007--1

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