首页 | 本学科首页   官方微博 | 高级检索  
     

基于UGF-Net的指尖检测模型
引用本文:刘佳,卞方舟,陈大鹏,李为斌. 基于UGF-Net的指尖检测模型[J]. 计算机工程与应用, 2022, 58(5): 225-231. DOI: 10.3778/j.issn.1002-8331.2010-0235
作者姓名:刘佳  卞方舟  陈大鹏  李为斌
作者单位:南京信息工程大学 自动化学院 B-DAT&CICAEET,南京 210044
基金项目:国家自然科学基金;江苏省产业前瞻与关键核心技术重点项目
摘    要:在人机交互领域,精确的人手指尖检测对交互的丰富度、灵活度有很大影响.然而,由于指尖的尺寸较小,精确、鲁棒的指尖检测目前仍然是一项颇具挑战性的任务.为了提升指尖检测的准确率与实时性,提出一种基于深度卷积神经网络的指尖检测模型UGF-Net(unified-gesture-and-fingertip-network).该模...

关 键 词:卷积神经网络  深度学习  指尖检测  手势识别  目标检测

Fingertip Detection Model Based on UGF-Net
LIU Jia,BIAN Fangzhou,CHEN Dapeng,LI Weibin. Fingertip Detection Model Based on UGF-Net[J]. Computer Engineering and Applications, 2022, 58(5): 225-231. DOI: 10.3778/j.issn.1002-8331.2010-0235
Authors:LIU Jia  BIAN Fangzhou  CHEN Dapeng  LI Weibin
Affiliation:B-DAT&CICAEET, School of Automation, Nanjing University of Information Science & Technology, Nanjing 210044, China
Abstract:In the field of human-computer interaction,accurate fingertip detection has a great impact on the richness and flexibility of interaction.However,due to the small size of fingertip,accurate and robust fingertip detection is still a challenging task.In order to improve the accuracy of fingertip detection,this paper proposes a fingertip detection model based on depth convolution neural network UGF-Net(unified-gesture-and-fingertip-network).The model can be used for fingertip detection and gesture recognition at the same time.The YOLO algorithm is used to extract the gesture area,and the FCNN output visual Gaussian heat map is used to realize fingertip detection.Finally,the effectiveness and robustness of the proposed fingertip detection model are verified by experiments.The model is tested on the SCUT-Ego-Gesture data set.The results show that the accuracy of fingertip detection can reach 99.8%,and the average frame rate of real-time video image is 34.5 frame/s,which meets the requirements of real-time.
Keywords:convolutional neural network  deep learning  fingertip detection  gesture recognition  target detection
本文献已被 维普 万方数据 等数据库收录!
点击此处可从《计算机工程与应用》浏览原始摘要信息
点击此处可从《计算机工程与应用》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号