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Real-time tracking of deformable objects based on MOK algorithm

Real-time tracking of deformable objects based on MOK algorithm
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摘要 The traditional oriented FAST and rotated BRIEF(ORB) algorithm has problems of instability and repetition of keypoints and it does not possess scale invariance. In order to deal with these drawbacks, a modified ORB(MORB) algorithm is proposed. In order to improve the precision of matching and tracking, this paper puts forward an MOK algorithm that fuses MORB and Kanade-Lucas-Tomasi(KLT). By using Kalman, the object's state in the next frame is predicted in order to reduce the size of search window and improve the real-time performance of object tracking. The experimental results show that the MOK algorithm can accurately track objects with deformation or with background clutters, exhibiting higher robustness and accuracy on diverse datasets. Also, the MOK algorithm has a good real-time performance with the average frame rate reaching 90.8 fps. The traditional oriented FAST and rotated BRIEF(ORB) algorithm has problems of instability and repetition of keypoints and it does not possess scale invariance. In order to deal with these drawbacks, a modified ORB(MORB) algorithm is proposed. In order to improve the precision of matching and tracking, this paper puts forward an MOK algorithm that fuses MORB and Kanade-Lucas-Tomasi(KLT). By using Kalman, the object's state in the next frame is predicted in order to reduce the size of search window and improve the real-time performance of object tracking. The experimental results show that the MOK algorithm can accurately track objects with deformation or with background clutters, exhibiting higher robustness and accuracy on diverse datasets. Also, the MOK algorithm has a good real-time performance with the average frame rate reaching 90.8 fps.
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2016年第2期477-483,共7页 系统工程与电子技术(英文版)
基金 supported by the National Natural Science Foundation of China(61471194) the Fundamental Research Funds for the Central Universities the Science and Technology on Avionics Integration Laboratory and Aeronautical Science Foundation of China(20155552050) the CASC(China Aerospace Science and Technology Corporation) Aerospace Science and Technology Innovation Foundation Project the Nanjing University of Aeronautics And Astronautics Graduate School Innovation Base(Laboratory)Open Foundation Program(kfjj20151505)
关键词 Kalman prediction oriented FAST and rotated BRIEF(ORB) match deformation real-time tracking Kalman prediction oriented FAST and rotated BRIEF(ORB) match deformation real-time tracking
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  • 1陈付幸,王润生.基于预检验的快速随机抽样一致性算法[J].软件学报,2005,16(8):1431-1437. 被引量:106
  • 2常勇,何宗宜.基于ARToolKit的地下管网增强现实系统研究[J].计算机工程与应用,2005,41(29):196-199. 被引量:10
  • 3管涛,李利军,王乘.增强现实开发工具ARDK的研究与应用[J].计算机工程与应用,2006,42(19):84-86. 被引量:4
  • 4Pintaric T. An adaptive thresholding algorithm for the aug- mented reality toolkit l C ]//IEEE International Augmented Reality Toolkit Workshop. 2003:71.
  • 5Ke Y, Sukthankar R. PCA-SIFT: A more distinctive repre- sentation for local image descriptors [ C ]// Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2004:506-513.
  • 6Bay H, Tuytelaars T, Van Cool L. SURF: Speeded up ro- bust features[ C ]//European Conference on Computer Vi- sion. 2006:404-417.
  • 7Rublee E, Rabaud V, Konolige K, et al. ORB: An effi- cient alternative to SIFT or SURF[ C]//2011 IEEE Inter- national Conference on Computer Vision (ICCV). 2011 2564-2571.
  • 8Rosten E, Drummond T. Machine learning for high-spee: corner detection[ C ]// European Conference on Compute1 Vision. 2006:430-443.
  • 9Calonder M, Lepetit V, Strecha C, et al. Brief: Binary ro- bust independent elementary features [ C ]// The 11 th Eu. ropean Conference on Computer Vision. 2010:778-792.
  • 10Wagner D, Reitmayr G, Mulloni A, et al. Real-time de- tection and tracking for augmented reality on mobile phones [J]. IEEE Transactions on Visualization and Computer Graphics, 2010,16(3 ) :355-368.

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