计算机应用研究2024，Vol.41Issue(1)：296-300,5.DOI:10.19734/j.issn.1001-3695.2023.07.0278
基于ToF红外图像的手部轻量化检测算法设计与优化
Design and optimization of hand lightweight detection algorithm based on ToF infrared images
摘要
Abstract
Implementing fast and accurate hand detection on embedded devices mainly face two challenges.Firstly,it is diffi-cult for complex deep learning networks to achieve real-time hand detection.Secondly,the complexity of the scene leads to a decrease in the accuracy of hand detection algorithms based on RGB color images.Unlike mainstream RGB image based detec-tion technologies,this paper adopted a lightweight hand detection algorithm based on ToF infrared images to attain precise and swift hand detection within the infrared images.Firstly,this paper gathered 22 419 static infrared images using this self-engineered equipment,thereby establishing an infrared dataset tailored for hand detection.Subsequently,it enhanced a gene-ral object detection algorithm to create a lightweight hand detection network known as RetinaHand,using two different light-weight networks,MobileNetV1 and ShuffleNetV2,as the backbone network of the model.Furthermore,this paper proposed an attention-enhanced feature pyramid structure called Attention-FPN.This structure integrated attention mechanisms to enhance the detection process.Ultimately,this paper conducted comparative experiments on the infrared dataset against conventional methods to validate the effectiveness of the method.关键词
深度学习/手部检测/红外图像/嵌入式设备Key words
deep learning/hand detection/infrared images/embedded devices分类
信息技术与安全科学引用本文复制引用
葛晨阳,马文彪,屈渝立..基于ToF红外图像的手部轻量化检测算法设计与优化[J].计算机应用研究,2024,41(1):296-300,5.基金项目
国家自然科学基金仪器课题(61627811) （61627811）
陕西省自然科学基金课题(2021JZ-04) （2021JZ-04）
陕西省重点研发高校联合项目(2021GXLH-Z-093) （2021GXLH-Z-093）
陕西省技术创新引导专项资助项目(2021QFY01-03) （2021QFY01-03）
