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SCIENCE CHINA Information Sciences, Volume 59 , Issue 4 : 042412(2016) https://doi.org/10.1007/s11432-015-5516-2

A low-complexity sensor fusion algorithm based on a fiber-optic gyroscope aided camera pose estimation system

More info
  • ReceivedSep 16, 2015
  • AcceptedOct 20, 2015
  • PublishedFeb 1, 2016

Abstract


Funded by

International S&T Cooperation Program of China(2015DFG12520)

National Natural Science Foundation of China(61571379)

National Natural Science Foundation of China(61275005)


References

[1] Klein G S W, Drummond T W. Image Vision Comput, 2004, 22: 769-776 CrossRef Google Scholar

[2] Hol J D. Pose Estimation and Calibration Algorithms for Vision and Inertial Sensors. Sweden Linköping: Linköping Univ Press, 2008. 7--23. Google Scholar

[3] Song S, Qiao W, Li B, et al. IEEE Trans Magn, 2014, 50: 4003707-776 Google Scholar

[4] Wang Q, Chen W P, Zheng R, et al. Inf Process Sens Netw, 2003, 2634: 642-657 CrossRef Google Scholar

[5] Zhang X, Hu W, Xie N, et al. Int J Comput Vis, 2015, 115: 279-304 CrossRef Google Scholar

[6] Zhang X, Hu W, Maybank S, et al. Sequential particle swarm optimization for visual tracking. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, Anchorage, 2008. 1--8. Google Scholar

[7] Li Y, Ai H, Yamashita T, et al. IEEE Trans Anal, 2008, 30: 1728-1740 Google Scholar

[8] Park I K, Singhal N, Lee M H, et al. IEEE Trans Parall Distr, 2011, 22: 91-104 CrossRef Google Scholar

[9] Erdem A T, Ercan A O. IEEE Trans Image Process, 2015, 24: 538-548 CrossRef Google Scholar

[10] Foxlin E. Inertial head-tracker sensor fusion by a complementary separate-bias Kalman filter. In: Proceedings of IEEE Virtual Reality Annual International Symposium, Santa Clara, 1996. 185--194. Google Scholar

[11] Hol J D, Dijkstra F, Luinge H, et al. Tightly coupled UWB/IMU pose estimation. In: Proceedings of IEEE International Conference on Ultra-Wideband, Vancouver, 2009. 688--692. Google Scholar

[12] He P, Cardou P, Desbiens A, et al. Multibody Syst Dyn, 2014, 35: 1-27 Google Scholar

[13] Corke P, Lobo J, Dias J. Int J Robot Res, 2007, 26: 519-535 CrossRef Google Scholar

[14] Starner T. IEEE Pervas Comput, 2013, 12: 14-16 Google Scholar

[15] Chai L, Nguyen K, Hoff B, et al. An adaptive estimator for registration in augmented reality. In: Proceedings of 2nd IEEE and ACM International Workshop on Augmented Reality, San Francisco, 1999. 23--32. Google Scholar

[16] You S, Neumann U. Fusion of vision and gyro tracking for robust augmented reality registration. In: Proceedings of IEEE Conference on Virtual Reality, Yokohama, 2001. 71--78. Google Scholar

[17] Zhang G. The Principles and Technologies of Fiber-Optic Gyroscope. Beijing: National Defense Industry Press, 2008. 1--25. Google Scholar

[18] Barbour N, Schmidt G. IEEE Sens J, 2001, 1: 332-339 CrossRef Google Scholar

[19] Hwangbo M, Kim J S, Kanade T. Int J Robot Res, 2011, 30: 1755-1774 CrossRef Google Scholar

[20] Yu J, Wang Z F. Sci China Inf Sci, 2014, 57: 029101-1774 Google Scholar

[21] Gonzalez R C, Woods R E, Eddins S L. Digital Image Processing Using Matlab. Beijing: Publishing House of Electronics Industry, 2014. 205--229. Google Scholar

[22] Wang X, He C, Wang Z. Opt Lett, 2011, 36: 1191-1193 CrossRef Google Scholar

[23] He C, Yang C, Wang Z. Opt Eng, 2012, 51: 124401-1193 CrossRef Google Scholar