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基于iOS设备的自主航拍巡检控制终端的设计 被引量:2

Design of autonomous aerial inspection client based on iOS devices
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摘要 针对无人机航拍巡检操作繁琐、效率低下等问题,提出了一种基于iOS设备和图像跟踪算法的无人机自主航拍巡检控制终端。使用无人机控制软件开发包搭建了终端与无人机、航拍云台、无线图像传输设备、无人机控制器之间的通信链路。基于FFmpeg实现视频解码,提出了基于自适应尺度的时空上下文跟踪算法,引入尺度参数变化率以在线纠正更新尺度参数的过激变化,大幅增强了航拍云台在复杂背景下的跟踪稳定性,实现了无人机航拍系统对不同尺度目标的自主、稳定跟踪,提高了航拍巡检效率。 A new design scheme of autonomous aerial inspection client based on iOS devices and object tracking algorithm for the complex and inefficient operation of traditional inspection system is presented. The communication link between the UAV, gimbal, wireless transmission system and the UAV controller is completed by Mobile SDK. Use FFmpeg lib in the decoding process. The a- daptive scale STC (spatio-temporal context) algorithm which can update scale parameters according to the tracking windows di- mension changing for object tracking is proposed. The experimental results show that the new client enhances the tracking stability comparing with the original inspection system in complex background situation, improves the efficiency of UVA inspection system.
出处 《电视技术》 北大核心 2016年第10期55-59,共5页 Video Engineering
关键词 无人机巡检 时空上下文 IOS 软件开发包 自适应尺度 unmanned aerial vehicle inspection spatio-temporal context lOS mobile SDK adaptive scale
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参考文献7

  • 1MIGUEL A, PASCUAL C, CAROL M, et al. A pan-tih camera fuzzy vision controller on an unmanned aerial vehi- cle [ C]//Proc. IEEE/RSJ Internation',d Conference on In- telligent Robots and Systems. [ S. 1. ] : IEEE, 2009:2879 -2884.
  • 2ZHANG K H, ZHANG L, YANG M H. A Fast compressive tracking [ J ]. IEEE transactions on pattern analysis and ma- chine intelligence, 2014, 36(10) : 2002-2015.
  • 3ZHANG K I4, ZHANG L, LIU Q S, et al. Fast visual track- ing via dense spatio-temporal context learning [ C ]//Proc. ECCV 2014. Cch Republic: Springer, 2014:127-141.
  • 4赵红超,李琦,韩瑾,李鼎.基于Android平台的实时监控系统客户端设计[J].电视技术,2015,39(20):111-114. 被引量:3
  • 5杨正洪,苏伟基.iPhone应用程序设计开发[M].北京:清华大学出版社,2007.
  • 6徐建强,陆耀.一种基于加权时空上下文的鲁棒视觉跟踪算法[J].自动化学报,2015,41(11):1901-1912. 被引量:33
  • 7HARRIS C, STEPHENS M. A combined comer and edge detector [ C ]// Proc. the 4th Alvey Vision Conference. [S. 1. ] :IEEE,1988:52-59.

二级参考文献32

  • 1王咸锋,林华.手机远程视频实时监控系统的设计与实现[J].微计算机信息,2007,23(34):111-112. 被引量:8
  • 2Babenko B, Yang M H, Belongie S. Robust object tracking with online multiple instance learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(8): 1619-1632.
  • 3Ross D A, Lim J, Lin R S, for robust visual tracking Yang M H. Incremental learning International Journal of Corn- purer Vision, 2008, 77(1-3): 125-141.
  • 4Zhang K H, Zhang L, Yang M H. Fast compressive track- ing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, 36(10): 2002-2015.
  • 5Kwon J, Lee K M. Visual tracking decomposition. In: Pro- ceedings of the 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). San Francisco, CA, USA: IEEE, 2010. 1269-1276.
  • 6Kalal Z, Mikolajczyk K, Matas J. Tracking-learning- detection. IEEE Transactions on Pattern Analysis and Ma- chine Intelligence, 2012, 34(7): 1409-1422.
  • 7Zhou X Z, Lu Y, Lu J W, Zhou J. Abrupt motion tracking via intensively adaptive Markov chain Monte Carlo sam- piing. IEEE Transactions on Image Processing, 2012, 21(2): 789-801.
  • 8Zhou T F, Lu Y, Di H J. Nearest neighbor field driven stochastic sampling for abrupt motion tracking. In: Pro- ceedings of the 2014 International Conference on Multime- dia and Expo (ICME). Chengdu China: IEEE, 2014. 1-6.
  • 9Grabner H, Matas J, Van Gool L, Cattin P. Tracking the in- visible: learning where the object might be. In: Proceedings of the 2010 IEEE Conference on Computer Vision and Pat- tern Recognition (CVPR). San Francisco, CA, USA: IEEE, 2010. 1285-1292.
  • 10Dinh T B, Vo N, Medioni G. Context tracker: exploring supporters and distracters in unconstrained environments. In: Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Colorado Springs, CO, USA: IEEE, 2011. 1177-1184.

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