[1]尚倩,阮秋琦,李小利.双目立体视觉的目标识别与定位[J].智能系统学报,2011,6(4):303-311.
SHANG Qian,RUAN Qiuqi,LI Xiaoli.Target recognition and location based on binocular stereo vision[J].CAAI Transactions on Intelligent Systems,2011,6(4):303-311.
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SHANG Qian,RUAN Qiuqi,LI Xiaoli.Target recognition and location based on binocular stereo vision[J].CAAI Transactions on Intelligent Systems,2011,6(4):303-311.
双目立体视觉的目标识别与定位
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
6
期数:
2011年第4期
页码:
303-311
栏目:
学术论文—机器感知与模式识别
出版日期:
2011-08-25
- Title:
- Target recognition and location based on binocular stereo vision
- 文章编号:
- 1673-4785(2011)04-0303-09
- Keywords:
- binocular stereo vision; camera calibration; image segmentation; stereo matching; binocular distance
- 分类号:
- TP18
- 文献标志码:
- A
- 摘要:
- 双目立体视觉系统可以实现对目标的识别与定位.此系统包含摄像机标定、图像分割、立体匹配和三维测距4个模块.在摄像机标定部分，提出了基于云台转角的外参数估计方法.该方法可以精确完成摄像头旋转情况下外参的估计,增强了机器人的视觉功能.并利用广茂达机器人系统，基于改进的双目视觉系统进行目标识别与定位，以此结果作为依据控制机器人的手臂进行相应运动，最终实现了对目标物体的抓取，验证了提出方法的可行性.
- Abstract:
- A binocular stereo vision system can be used for target recognition and location. This system consists of four modules, namely camera calibration, image segment, stereo matching, and binocular distance. furthermore, in the calibration section, a method of estimating the outer parameters based on the head angle was studied. In the experiment, this method could estimate the outer parameters accurately when the camera rotated, enhancing the vision function of the system. Then this improved binocular system was realized by the Grandar Robot platform. It was used for target recognition and location, and the results were used to control the robot motion. In the end, the target could be captured successfully, so the proposed method was proven to be feasible.
- 参考文献/References:
- ［1］祝琨.基于双目视觉的运动物体实时跟踪与测距［D］.北京：北京交通大学， 2008： 1103. ZHU Kun. Realtime tracking and measuring of moving object based on binocular vision［D］. Beijing: Beijing Jiaotong University, 2008: 1103.［2］ZHANG Zhengyou. Flexible camera calibration by viewing a plane from unknown orientations［C］//Proceedings of the IEEE International Conference on Computer Vision. Kerkyra, 1999: 666673. ［3］吴亚鹏.基于双目视觉的运动目标跟踪与三维测量［D］. 西安：西北大学， 2008： 158. WU Yapeng. Moving objects tracking and 3D measurement based on binocular vision［D］. Xi’an: Northwest University, 2008: 158. ［4］CHEN Yuming. Research on binocular 3D measurement model based on grating projection［C］//PEITS 2009—2009 2nd Conference on Power Electronics and Intelligent Transportation System. Shenzhen, China, 2009: 306308. ［5］ZHANG Zhengyou. A flexible new technique for camera calibration［J］. IEEE Transactions Pattern Analysis and Machine Intelligence, 2000, 22(11): 13301334. ［6］瞿中.图像分割与评价及图像三维表面重建研究［D］.重庆：重庆大学， 2009： 1108. QU Zhong. Research on image segmentation, evaluation and image threedimensional surface reconstruction［D］.Chongqing: Chongqing University, 2009: 1108. ［7］ZHAO Peng, NI Guoqiang. Simultaneous perimeter measurement for 3D object with a binocular stereo vision measurement system［J］. Optics and Lasers in Engineering, 2010, 48(4): 505511.［8］肖南峰.智能机器人［M］.广州：华南理工大学出版社，2008: 1098. ［9］蔡健荣,范军,李玉良.立体视觉系统标定及成熟果实定位［J］. 农机化研究, 2007， 11： 3841. CAI Jianrong, FAN Jun, LI Yuliang. Binocular system calibration and mature fruit location［J］. Agricultural Research, 2007, 11: 3841. ［10］周子啸,赵晓林，胡峰,等.基于仿真机器人的双目视觉定位［J］.电视技术， 2010, 8: 106109. ZHOU Zixiao, ZHAO Xiaolin, HU Feng, et al. Binocular stereo location on emulator robot［J］.TV Technology, 2010, 8: 106109. ［11］郭巍，张平，朱良，陈曦. 基于AdaBoost.ECOC的合成孔径雷达图像目标识别研究［J］. 哈尔滨工程大学学报, 2010, 31(2): 232236. GUO Wei, ZHANG Ping, ZHU Liang, CHEN Xi. Research on synthetic aperture radar image target recognition based on AdaBoost.ECOC［J］. Journal of Harbin Engineering University, 2010, 31(2): 232236.［12］王科俊， 魏娟. 基于共面圆的双目立体视觉分步标定法［J］. 应用科技, 2010, 37(1): 3640. WANG Kejun， WEI Juan. Binocular stereo vision step by step calibration based on coplanar circle［J］. Applied Science and Technology, 2010, 37(1): 3640.
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备注/Memo
收稿日期：2010-12-09.
基金项目：国家自然科学基金资助项目（60973060）;高等学校博士学科点专项科研基金资助项目(20080004001).
通信作者：尚倩.E-mail:renxuefeier@gmail.com.
作者简介：
尚倩，女，1987年生，硕士研究生，主要研究方向为计算机视觉、数字图像处理、信号与信息处理.
阮秋琦,男,1944 年生,教授,博士生导师,北京交通大学信息科学研究所所长, IEEE高级会员. 主要研究方向为图像处理、计算机视觉、多媒体信息处理、虚拟现实、计算机支持的协同工作. 曾获国家教委科技进步二等奖、铁道部科技进步二等奖和三等奖等. 发表学术论文150余篇,出版著作3部,获国家专利1项.
李小利，女，1986年生，博士研究生，主要研究方向为数字图像处理、计算机视觉和模式识别.
更新日期/Last Update:
2011-09-30