摘要
在虚拟装配领域中,提升用户体验和交互精度一直是研究的重点。在利用Azure Kinect人体跟踪技术获取手部信息的基础上,研究利用SVM算法提高手势识别准确率的方法,通过参数寻优进一步优化了参数模型。在Unity3D平台上开发了虚拟装配系统,将优化后的手势识别应用在虚拟装配系统中并实现了主要装配功能,同时加入语音识别进行辅助装配。实验结果表明:通过SVM算法优化后,手势识别更加准确、稳定,提升了虚拟装配系统的用户体验和交互准确性。
In the field of virtual assembly,improving user experience and interaction accuracy has been the focus of research.Based on using Azure Kinect human tracking technology to obtain hand information,SVM algorithm was studied to improve the accuracy of gesture recognition and the parameter model was further optimized through parameter optimizing.A virtual assembly system was developed on Unity3D platform,and the optimized gesture recognition was applied to the virtual assembly system.The main assembly functions were implemented,while speech recognition was added to assist the assembly.The experimental results show that the gesture recognition is more accurate and stable after the optimization by SVM algorithm,which improves the virtual assembly system’s user experience and interaction accuracy.
作者
张天洋
范劲松
ZHANG Tianyang;FAN Jinsong(School of Mechatronic Engineering and Automation,Foshan University,Foshan Guangdong 528000,China;School of Industrial Design and Ceramic Art,Foshan University,Foshan Guangdong 528000,China)
出处
《机床与液压》
北大核心
2022年第18期67-72,共6页
Machine Tool & Hydraulics
基金
国家文化和旅游科技创新工程项目(2019-010)。
