基于单目视觉的四旋翼飞行器目标跟踪算法研究

doi:10.3969/j.issn.1000-1158.2018.03.11

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Abstract Taking AR.drone four-rotor aircraft as a research platform, a method based on AR.drone front-end monocular camera and Calman filter is proposed to track moving target in video. The RGB image obtained through color space conversion paired illumination changes HSV image is on the image by OpenCV,the OpenCV of image denoising for target tracking in the video images is used, and then detect and find the largest contour of targets in images and use the Kalman filter to modify the target location. Then the flight direction of the quadrotor is calculated to realize the tracking of the moving target in the video area of the quadrotor. The experimental results show that this method is effective for moving target tracking accuracy, stability and rapidity.

Key words： metrology monocular camera four-rotor aircraft color space conversion Kalman filter OpenCV target tracking

Received: 28 June 2016 Published: 12 April 2018

PACS:	TB96
	TB973

Corresponding Authors: Mei JIN E-mail: meijin297@126.com

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	ZHANG Li-guo
	LI Xiao-song
	XIAO Lei
	JIN Mei
	DONG Hao

Cite this article:

ZHANG Li-guo,LI Xiao-song,XIAO Lei, et al. Research on Target Tracking Algorithm of the Quadrotor Aircraft Based on Monocular Vision[J]. Acta Metrologica Sinica, 2018, 39(3): 342-347.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2018.03.11 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2018/V39/I3/342

［1］李培华. 序列图像中运动目标跟踪方法［M］. 北京:科学出版社, 2010.
［2］Comaniciu D, Ramesh V, Meer P. Real-time tracking of non-rigid objects using Mean Shift［C］//Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition,New York:IEEE Press, 2000, 2:142-149.
［3］Nouar O D, Ali G, Raphael C. Improved object tracking with Camshift algorithm［C］//Proceedings of the IEEE International Conference on Acoustics,Speech,and Signal Processing. Toulouse,France:IEEE,2006.2(II):657-660.
［4］Baker S, Matthews I. Lucas-Kanade 20 Years On:A Unifying Framework［J］. International Journal of Computer Vision,2004,56(3):221-255.
［5］Dalal N,Triggs B. Histograms of oriented gradients forhuman detection［J］.IEEE Conference on Computer Vision & Pattern Recognition, 2005, 1(12):886-893.
［6］Kalal Z, Mikolajczyk K, Matas J. Tracking learningdetection［J］. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2012, 34(7):1409-1422.
［7］吴风和. 基于计算机视觉测量技术的图像轮廓提取方法研究［J］. 计量学报, 2007, 28(1):18-22.
［8］黄桂平, 李广云, 王保丰. 单目视觉测量技术研究［J］. 计量学报, 2004, 25(4):314-317.
［9］吕强, 倪佩佩, 刘峰. 基于视觉的四旋翼飞行器路径跟踪［J］. 四川兵工学报, 2014, 35(11):106-109.
［10］Pestana J, Sanchez-Lopez J, Saripalli S, et al. Computer vision based general object following for GPS-denied multirotor unmanned vehicles［C］// American Control Conference (ACC). Oregon,USA:IEEE,2014.
［11］Hajiyev C, Soken H E. Robust Adaptive Kalman Filter for estimation of UAV dynamics in the presence of sensor/actuator faults［J］. Aerospace Science and Technology, 2013, 28(1):376-383.
［12］权太范. 目标跟踪新理论［M］. 北京:国防工业出版社, 2009.
［13］黄小平. 卡尔曼滤波原理及其应用［M］. 北京:电子工业出版社, 2015.
［14］田源,王洪涛. 基于量子核聚类算法的图像边缘特征提取研［J］. 计量学报,2016, 37(6): 582-586.
［15］仝晓龙, 窦腾飞, 刘艳红. 运动目标跟踪技术综述［J］. 科技创新与应用, 2014,(18):18-20.