基于机器视觉的人机交互系统的设计
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摘要
基于深度图像信息的获取与处理技术,实时性、鲁棒性较强,具有易于实现、交互性较好等优点.基于Kinect感应器的人机交互系统,可以实时捕捉深度图像和RGB图像,并运用Open NI和NITE技术框架,识别人体手势和关节运动姿态,最后将对应的操控指令发送至单片机执行,实现以自然体感的方式控制机器人.该系统易于实现、交互性较好,可以广泛应用于服务机器人、智能家居、工业控制等领域.
The acquisition and processing technology based on depth image information had real-time and strong robustness,it had the advantages of easy implementation and good interactivity. The human-computer interaction system based on Kinect sensor can capture depth image and RGB image in real time. We used the OpenNI and NITE technology framework to identify human gestures and joint motion posture,and finally send the corresponding control instructions to the single chip microcomputer for execution to realize control of the robot in a natural sense. The system was easy to implement and more interactive. It can be widely used in service robots,smart homes,industrial control and other fields.
The acquisition and processing technology based on depth image information had real-time and strong robustness,it had the advantages of easy implementation and good interactivity. The human-computer interaction system based on Kinect sensor can capture depth image and RGB image in real time. We used the OpenNI and NITE technology framework to identify human gestures and joint motion posture,and finally send the corresponding control instructions to the single chip microcomputer for execution to realize control of the robot in a natural sense. The system was easy to implement and more interactive. It can be widely used in service robots,smart homes,industrial control and other fields.
引文
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[9] BI X J,ZHAI S M. Bayesian touch:a statistical criterion of target selection with finger touch[J]. UIST'13 proceedings of the 26thannual ACM symposium on user interface software and technology[C]. New York:ACM Press,2013:51-60.
[10]路璐,田丰,戴国忠,等.融合触、听、视觉的多通道认知和交互模型[J].计算机辅助设计与图形学学报,2014,26(4):654-661.
[11]张雪华,刘华平,孙富春,等.采用Kinect的移动机器人目标跟踪[J].智能系统学报,2014,9(1):34-39.
[12]于振中,郑为凑,刘鑫,等.基于Kinect的移动机器人实时局部路径规划[J].计算机工程,2013,39(4):243-247.
[13]李飞龙,王宇俊,谭艳,等.一种基于Kinect的自动跟随机器人设计[J].电脑知识与技术:学术交流,2013,9(13):3125-3128.
[2] CROWLEY J,COUTAZ J,BRARD F. Things that see:machine perception for human computer interaction[J].Communications of the ACM,2000,43(3):54-64.
[3]徐光祐,陶霖密,史元春,等.普适计算模式下的人机交互[J].计算机学报,2007,30(7):1041-1053.
[4]刘杰,黄进,田丰,等.连续交互空间下的混合手势交互模型[J].软件学报,2017,28(8):2080-2095.
[5]李文生,解梅,邓春健.基于多点手势识别的人机交互技术框架[J].计算机工程与设计,2011,32(6):2129-2133.
[6]雷超,戴国忠.三维交互体系结构的研究与实现[J].计算机研究与发展,2001,38(5):557-562.
[7] KULJIC B,JANOS S,TIBOR S. Mobile robot controlled by voice[J]. International Symposium on Intelligent Systems and Informatics,2007:189-192.
[8]孙艺红,刘媛.服务机器人语音交互解决方案[J].控制工程,2004,11(2):184-186.
[9] BI X J,ZHAI S M. Bayesian touch:a statistical criterion of target selection with finger touch[J]. UIST'13 proceedings of the 26thannual ACM symposium on user interface software and technology[C]. New York:ACM Press,2013:51-60.
[10]路璐,田丰,戴国忠,等.融合触、听、视觉的多通道认知和交互模型[J].计算机辅助设计与图形学学报,2014,26(4):654-661.
[11]张雪华,刘华平,孙富春,等.采用Kinect的移动机器人目标跟踪[J].智能系统学报,2014,9(1):34-39.
[12]于振中,郑为凑,刘鑫,等.基于Kinect的移动机器人实时局部路径规划[J].计算机工程,2013,39(4):243-247.
[13]李飞龙,王宇俊,谭艳,等.一种基于Kinect的自动跟随机器人设计[J].电脑知识与技术:学术交流,2013,9(13):3125-3128.