Federated Filter Algorithm with Positioning Technique Based on 3D Sensor (original) (raw)

References

1. L.A. Alexandre, Gender recognition: a multiscale decision fusion approach. Pattern Recognit. Lett. 31(11), 1422–1427 (2010)
   Article Google Scholar
2. J. Atkins, D.P. Sharma, Visualization of babble-speech interactions using Andrews curves. Circuits Syst. Signal Process. 35(4), 1313–1331 (2016)
   Article MathSciNet Google Scholar
3. M.C. Best, T.J. Gordon, P.J. Dixon, An extended adaptive Kalman filter for real-time state estimation of vehicle handling dynamics. Veh. Syst. Dyn. 34(1), 57–75 (2000)
   Article Google Scholar
4. E. Cao, K. Jiang, Adaptive unscented Kalman filter for input estimations in diesel-engine selective catalytic reduction systems. Neurocomputing 205, 329–335 (2016)
   Article Google Scholar
5. G. Chen, J. Li, B. Wang et al., Reconstructing 3D human models with a KINECT. Comput. Anim. Virtual Worlds 27(1), 72–85 (2016)
   Article Google Scholar
6. M. Glodek, F. Honold, T. Geier et al., Fusion paradigms in cognitive technical systems for human–computer interaction. Neurocomputing 161, 17–37 (2015)
   Article Google Scholar
7. X.L. Gong, J.X. Zhang, An innovative transfer alignment method based on federated filter for airborne distributed POS. Measurement 86, 165–181 (2016)
   Article Google Scholar
8. C. Hajiyev, H.E. Soken, Robust adaptive Kalman filter for estimation of UAV dynamics in the presence of sensor/actuator faults. Aerosp. Sci. Technol. 28(1), 376–383 (2013)
   Article Google Scholar
9. H. Hasan, S. Abdul-Kareem, Human–computer interaction using vision-based hand gesture recognition systems: a survey. Neural Comput. Appl. 25(2), 251–261 (2014)
   Article Google Scholar
10. S.C. Hsu, J.Y. Huang, W.C. Kao et al., Human body motion parameters capturing using KINECT. Mach. Vis. Appl. 26(7–8), 919–932 (2015)
    Article Google Scholar
11. T.E. Hutchinson, K.P. White, W.N. Martin et al., Human–computer interaction using eye-gaze input. IEEE Trans. Syst. Man Cybern. 19(6), 1527–1534 (1989)
    Article Google Scholar
12. D. Kastaniotis, I. Theodorakopoulos, C. Theoharatos et al., A framework for gait-based recognition using KINECT. Pattern Recognit. Lett. 68, 327–335 (2015)
    Article Google Scholar
13. Z.H. Khan, I.Y. Gu, A.G. Backhouse, Robust visual object tracking using multi-mode anisotropic mean shift and particle filters. IEEE Trans. Circuits Syst. Video Technol. 21(1), 74–87 (2011)
    Article Google Scholar
14. F.K. Lang, J. Yang, D. Li et al., Mean-shift-based speckle filtering of polarimetric SAR data. IEEE Trans. Geosci. Remote Sens. 52(7), 4440–4454 (2014)
    Article Google Scholar
15. I. Leichter, M. Lindenbaum, E. Rivlin, Mean shift tracking with multiple reference color histograms. Comput. Vis. Image Underst. 114(3), 400–408 (2010)
    Article Google Scholar
16. P.J. Manuel, C. Saguees, E. Montijano et al., Human–computer interaction based on hand gestures using RGB-D sensors. Sensors 13(9), 11842–11860 (2013)
    Article Google Scholar
17. S. Mariani, A. Ghisi, Unscented Kalman filtering for nonlinear structural dynamics. Nonlinear Dyn. 49(1–2), 131–150 (2007)
    Article MATH Google Scholar
18. A.H. Mazinan, A. Amir-Latifi, Applying mean shift, motion information and Kalman filtering approaches to object tracking. ISA Trans. 51(3), 485–497 (2012)
    Article Google Scholar
19. H. Menegaz, J.Y. Ishihara, G.A. Borges et al., A systematization of the unscented Kalman filter theory. IEEE Trans. Autom. Control 60(10), 2583–2598 (2015)
    Article MathSciNet MATH Google Scholar
20. A. Motwani, S.K. Sharma, R. Sutton et al., Application of artificial neural networks to weighted interval Kalman filtering. Proc. Inst. Mech. Eng. Part I J. Syst. Control Eng. 228(5), 267–277 (2014)
    Article Google Scholar
21. S. Mure, T. Grenier, S.Dominik Meier et al., Unsupervised spatio-temporal filtering of image sequences. A mean-shift specification. Pattern Recognit. Lett. 68, 48–55 (2015)
    Article Google Scholar
22. J. Ning, L. Zhang, D. Zhang et al., Robust mean-shift tracking with corrected background weighted histogram. IET Comput. Vis. 6(1), 62–69 (2010)
    Article MathSciNet Google Scholar
23. G. Paravati, V. Gatteschi, Human–computer interaction in smart environments. Sensors 15(8), 19487–19494 (2015)
    Article Google Scholar
24. S.L. Phung, A. Bouzerdoum, A pyramidal neural network for visual pattern recognition. IEEE Trans. Neural Netw. 18(2), 329–343 (2007)
    Article Google Scholar
25. O. Straka, J. Dunik, M. Simandl, Unscented Kalman filter with advanced adaptation of scaling parameter. Automatica 50(10), 2657–2664 (2014)
    Article MathSciNet MATH Google Scholar
26. J.R. Terven, B. Raducanu, M. Elena Meza-de-Luna et al., Head-gestures mirroring detection in dyadic social interactions with computer vision-based wearable devices. Neurocomputing 175(SI), 866–876 (2016)
    Article Google Scholar
27. L.G. Wang, G.Y. Liu, Q.L. Dai, Optimization of segmentation algorithms through mean-shift filtering preprocessing. IEEE Geosci. Remote Sens. Lett. 11(3), 622–626 (2014)
    Article Google Scholar
28. C. Wu, X. Wang, Y. Guo et al., Robust uncertainty control of the simplified Kalman filter for acoustic echo cancelation. Circuits Syst. Signal Process. 35(12), 4584–4595 (2016)
    Article MathSciNet MATH Google Scholar
29. Z. Xiong, J.H. Chen, R. Wang et al., A new dynamic vector formed information sharing algorithm in federated filter. Aerosp. Sci. Technol. 29(1), 37–46 (2013)
    Article Google Scholar
30. B. Xu, Y. Guo, Y. Yuan et al., Fault-tolerant control using command-filtered adaptive back-stepping technique: application to hypersonic longitudinal flight dynamics. Int. J. Adapt. Control Signal Process. 30(4), 553–577 (2016)
    Article MathSciNet Google Scholar
31. L. Yu, G. Dai, S. Fei, Contactless multi-touch interactive technology based on adaptive filtering algorithm. Proc. Inst. Mech. Eng. Part I J. Syst. Control Eng. 231(9), 685–692 (2017)
    Article Google Scholar
32. L. Yu, S. Fei, G. Yang, A neural network approach for tracking control of uncertain switched nonlinear systems with unknown dead-zone. Circuits Syst. Signal Process. 34(8), 2695–2710 (2015)
    Article MathSciNet MATH Google Scholar
33. L. Yu, J. Huang, S. Fei, Sliding mode switching control of manipulators based on disturbance observer. Circuits Syst. Signal Process. 36, 2574–2585 (2017)
    Article MathSciNet MATH Google Scholar
34. K. Yu, N.R. Watson, J. Arrillaga, An adaptive Kalman filter for dynamic harmonic state estimation and harmonic injection tracking. IEEE Trans. Power Deliv. 20(2), 1577–1584 (2005)
    Article Google Scholar
35. Y. Yu, H. Zhao, B. Chen, A new normalized subband adaptive filter algorithm with individual variable step sizes. Circuits Syst. Signal Process. 35(4), 1407–1418 (2016)
    Article MathSciNet Google Scholar
36. W. Zhang, M.L. Smith, L.N. Smith et al., Gender and gaze gesture recognition for human–computer interaction. Comput. Vis. Image Underst. 149, 32–50 (2016)
    Article Google Scholar

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