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尺度旋转相关滤波视觉伺服研究

Research of Scale and Rotation Based Correlation Filter Visual Servo
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摘要 为了满足工业现场日益增多的应用需求,提高视觉伺服目标跟踪算法应用性,研究并提出了一种尺度旋转相关滤波视觉伺服实现方法。通过对MOSSE、ASET等先进算法进行改进,利用仿射原理,嵌入尺度旋转独立滤波器,构建适合工业现场的尺度相关滤波视觉伺服实现方法及实验平台,该实验平台由视觉伺服和二维运动控制平台组成,视觉伺服的输入为实时图像,输出为机器人动作;二维运动控制平台准确驱动被跟踪的目标,使跟踪结果可以量化。实验证明:该视觉伺服实现方法在改进鲁棒性和实时性的同时,可以满足工业现场应用需求。 In order to satisfy the increasing demand of industrial field and to improve the applicability of visual servo target tracking algorithm,a scale rotation correlation filter based visual servo implementation method is researched and designed.By improving the MOSSE,ASET and other advanced algorithm,affine principle was embedded into scale rotation independent filter to construct a scale related filter visual servo implementation method and experimental platform which is suitable for industrial field.The experimental platform was composed of visual servo and two-dimensional(2D)motion control platform.The input of visual servo was real-time image,and output was robot action.The 2D motion control platform accurately driven the target being tracked,so that the tracking result could be quantified.The experimental results show that this method improves the robustness and real-time performance,and can meet the needs of industrial field application.
作者 邓嘉明 侯跃恩 DENG Jiaming;HOU Yueen(Information Network Center,Jiaying University,Meizhou Guangdong 514015,China;School of Computer,Jiaying University,Meizhou Guangdong 514015,China)
出处 《机床与液压》 北大核心 2019年第14期159-162,166,共5页 Machine Tool & Hydraulics
基金 广东省省级科技计划项目(2015A030401104 2015B090906016 2016B010122034 2017B090906003)
关键词 尺度 旋转 相关滤波 视觉伺服 Scale Rotation Correlation filter Visual servo
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  • 1侯志强,韩崇昭.视觉跟踪技术综述[J].自动化学报,2006,32(4):603-617. 被引量:253
  • 2宋长新, 马克, 秦川, 肖鹏.2013,物理学报,62 040702.
  • 3Yilmaz A, Javed O, Shah M. Object tracking: a survey [ J]. ACM Computing Surveys,2006,38(4) : 1158-1166.
  • 4Wright J, Yang Allen Y, Arvind G, et al. Robust face reco- gnition via sparse representation [ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009,31 (2) :210-227.
  • 5Zhang L, Yang M, Feng X C. Sparse representation or col- laborative representation: which helps face recognition [ C] //IEEE International Conference on Computer Vi- sion. Barcelona : IEEE ,2011:471-478.
  • 6Yang M, Zhang L, Zhang D, et al. Relaxed collaborative representation for pattern classification [ C ]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Providence : IEEE, 2012 :2224-2231.
  • 7Mei X, Ling H B. Robust visual tracking and vehicle classi- fication via sparse representation [ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011,33 ( 11 ) :2259-2272.
  • 8Mei X,Ling H B. Robust visual tracking using l minimi- zation [ C ]//Proceedings of 2009 IEEE 12th International Conference on Computer Vision. Kyoto : IEEE ,2009 : 1436- 1443.
  • 9Bai T X, Li Y F. Robust visual tracking with structured sparse representation appearance model [ J ]. Pattern Reco- gnition,2012,45 (6) :2390-2404.
  • 10Xu J, Lu H C, Yang M H. Visual tracking via adaptive structural local sparse appearance model [ C ]//Proceed- ings of the IEEE Computer Society Conference on Com- puter Vision and Pattern Recognition. Providence : IEEE, 2012 : 1822-1829.

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