摘要
设计了一种基于Kinect手势识别的智能小车控制系统,利用Kinect体感设备的景深图像采集技术来获取人体动作的图像,通过阈值分割技术将手和人的身体分隔开,得到手部的图像信息,然后采用传统Kalman滤波技术对动态手势动作进行处理,利用NITE＋Open IN开发框架对Kinect获取的图像信息进行解析、处理;最后,计算机通过WiFi模块将获取的数据信息发送到智能小车上,实现了人体的手势动作远程操控智能小车完成对应指令动作。实验结果表明,由于采用了手势识别技术,减少了大量繁琐复杂的程序,使智能小车运行更加稳定、可靠。
Designing a smart car control system based on Kinect gesture recognition.The depth image acquisition technology of Kinect somatosensory equipment is used to acquire the images of human motion,Threshold segmentation technology is used to separate the hand and human body to obtain the image information of the hand.Then the traditional Kalman filtering technology is used to process the dynamic gestures.Then the image information obtained by the Kinect is analyzed using the NITE ＋ Open IN development analysis、processing;Finally,the computer uses the WiFi module to send the acquired data information to the smart car and realizes the human body′s gesture action to remotely control the smart car to complete the corresponding command action.The experimental results show that due to the use of gesture recognition technology,a large number of cumbersome and complicated procedures are reduced,making the smart car more stable and reliable.
作者
杨琼楠
张苗苗
杨聪锟
陈超波
Yang Qiongnan;Zhang Miaomiao;Yang Congkun;Chen Chaobo(School of Electronic and Information Engineering,Xi＇an Technological University,Xi＇an 710016,China;Northwest Institute of Mechanical and Electrical Engineering,Xianyang 712099,China)
出处
《国外电子测量技术》
2018年第9期85-89,共5页
Foreign Electronic Measurement Technology
基金
陕西省国际科技合作基地项目(2017GHJD-009)
陕西省教育厅科研计划项目)(16JF013)资助
