Multi-Scale Detection Method for Soldier and Armored Vehicle Objects

被引：0
|
作者：
Wang J. [1 ]
Wang J. [1 ]
Yu Z. [1 ]
Wang H. [1 ]
机构：
[1] School of Mechatronical Engineering, Beijing Institute of Technology, Beijing
来源：
Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology | 2023年 / 43卷 / 02期
关键词：
data augmentation; mutil-scale object detection; small object detection;
D O I：
10.15918/j.tbit1001-0645.2022.022
中图分类号：
学科分类号：
摘要：
A multi-scale object detection method was proposed based on YOLOv4 deep learning algorithm to solve the multi-scale problem caused by the huge-scale difference between soldiers and armored vehicles, as well as object distance. The diversity of small object samples was enriched through targeted data augmentation methods input images were segmented to improve the resolution of input small objects of network, the detection results of large, medium and small objects were separated based on the feature pyramid network, and finally the detection results were matched and NMS processing was carried out to remove the redundant detection boxes, so as to achieve multi-scale object detection. The experimental results show that the average mean precision of small and medium objects is improved by 1.20% and 5.54% respectively, while the detection effect of large objects is maintained, which effectively improves the detection effect of small and medium objects. © 2023 Beijing Institute of Technology. All rights reserved.
引用
收藏
页码：203 / 212
页数：9
相关论文
共 16 条
  • [11] HAN Zishuo, WANG Chunping, FU Qiang, Ship detection in SAR images based on deep feature enhancement network, Transactions of Beijing Institute of Technology, 41, 9, pp. 1006-1014, (2021)
  • [12] SUN Haoze, CHANG Tianqing, ZHANG Lei, Et al., Tank and armored target detection based on top-down network, Computer Simulation, 37, 3, pp. 18-22, (2020)
  • [13] BOCHKOVSKIY A, WANG C Y, LIAO H Y., YOLOv4: optimal speed and accuracy of object detection
  • [14] LI Weihao, YAO Shiming, LI Yuqing, Et al., A motion reconstruction technology for distributed collaborative plotting of AR sand table, Transactions of Beijing Institute of Technology, 39, 12, pp. 1298-1303, (2019)
  • [15] WANG Fenhua, HUANG Chao, ZHAO Bo, Et al., Gesture recognition based on YOLO algorithm, Transactions of Beijing Institute of Technology, 40, 8, pp. 873-879, (2020)
  • [16] WU Haomin, Research and implementation of road traffic sign recongition based on driving video, (2020)
12