电子科技2024，Vol.37Issue(4)：77-86,10.DOI:10.16180/j.cnki.issn1007-7820.2024.04.011
基于锚点的快速三维手部关键点检测算法
Research on Fast 3D Hand Keypoint Detection Algorithm Based on Anchor
摘要
Abstract
In human-robotcollaboration tasks,hand key point detection provides target point coordinates for the robotic arm.A2J(Anchor-to-Joint)is a representative method of key point detection using anchor points.A2J can achieve better detection effect with depth map input,but it has insufficient ability to acquire global features.In this study,a GLF(Global-Local Feature Fusion)module is designed to fuse the shallow and deep features of the backbone network.In order to improve the detection speed,the backbone network of A2J is replaced with Shuffle-Netv2 and reformed,and 3×3 depth separable convolution is replaced with 5×5 depth separable convolution to in-crease the sensitivity field and effectively improve the backbone network's ability to extract global features.ECA(Effi-cient Channel Attention)is introduced into the anchor weight estimation branch to improve the network's attention to important anchor points.The results of training and testing on the mainstream data sets ICVL and NYU show that the average error of the proposed method is reduced by 0.09 mm and 0.15 mm,respectively,compared with A2J.The detection rate of 151 frame·s-1 is realized on GTX1080Ti graphics card,which fully meets the real-time require-ment of man-machine collaboration task.关键词
人机协作/三维手部关键点检测/锚点/深度图/全局-局部特征融合/ShuffleNetv2/深度可分离卷积/高效通道注意力Key words
human-robot collaboration/3D hand keypoint detection/anchor point/depth map/global-local feature fusion/ShuffleNetv2/depthwise separable convolution/efficient channel attention分类
信息技术与安全科学引用本文复制引用
秦晓飞,何文,班东贤,郭宏宇,于景..基于锚点的快速三维手部关键点检测算法[J].电子科技,2024,37(4):77-86,10.基金项目
国家自然科学基金(92048205) （92048205）
国家留学基金(202008310014)National Natural Science Foundation of China(92048205) （202008310014）
China Scholarship(202008310014) （202008310014）
