Table of Contents Author Guidelines Submit a Manuscript
Journal of Electrical and Computer Engineering
Volume 2018, Article ID 5381962, 9 pages
https://doi.org/10.1155/2018/5381962
Research Article

Target Tracking via Particle Filter and Convolutional Network

1College of Automation, Harbin Engineering University, Harbin, China
2College of Electrical and Information Engineering, Heilongjiang Institute of Technology, Harbin, China

Correspondence should be addressed to Hongxia Chu; moc.361@0240xhc

Received 3 June 2017; Revised 17 August 2017; Accepted 14 November 2017; Published 9 January 2018

Academic Editor: Tongliang Liu

Copyright © 2018 Hongxia Chu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. Yilmaz, O. Javed, and M. Shah, “Object tracking: a survey,” ACM Computing Surveys, vol. 38, no. 4, article 13, 2006. View at Publisher · View at Google Scholar · View at Scopus
  2. X. Ben, W. Meng, and R. Yan, “Dual-ellipse fitting approach for robust gait periodicity detection,” Neurocomputing, vol. 79, pp. 173–178, 2012. View at Publisher · View at Google Scholar · View at Scopus
  3. A. D. Jepson, D. J. Fleet, and T. F. El-Maraghi, “Robust online appearance models for visual tracking,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 10, pp. 1296–1311, 2003. View at Publisher · View at Google Scholar · View at Scopus
  4. D. A. Ross, J. Lim, R.-S. Lin, and M.-H. Yang, “Incremental learning for robust visual tracking,” International Journal of Computer Vision, vol. 77, no. 1–3, pp. 125–141, 2008. View at Publisher · View at Google Scholar · View at Scopus
  5. T. Liu and D. Tao, “Classification with Noisy Labels by Importance Reweighting,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 38, no. 3, pp. 447–461, 2016. View at Publisher · View at Google Scholar · View at Scopus
  6. T. L. Liu, Q. Yang, and D. C. Tao, “Understanding how feature structure transfers in transfer learning,” in Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, pp. 2365–2371, Melbourne, Australia, 2017. View at Publisher · View at Google Scholar
  7. M. Nieto, A. Cortés, O. Otaegui, J. Arróspide, and L. Salgado, “Real-time lane tracking using Rao-Blackwellized particle filter,” Journal of Real-Time Image Processing, vol. 11, no. 1, pp. 179–191, 2016. View at Publisher · View at Google Scholar · View at Scopus
  8. M. Lucena, J. M. Fuertes, and N. P. de la Blanca, “Optical flow-based observation models for particle filter tracking,” PAA. Pattern Analysis and Applications, vol. 18, no. 1, pp. 135–143, 2015. View at Publisher · View at Google Scholar · View at MathSciNet
  9. M. E. Yildirim, I. F. Ince, Y. B. Salman, J. K. Song, J. S. Park, and B. W. Yoon, “Direction-Based Modified Particle Filter for Vehicle Tracking,” ETRI Journal, vol. 38, no. 2, pp. 356–365, 2016. View at Publisher · View at Google Scholar · View at Scopus
  10. J. Kwon and K. M. Lee, “Visual tracking decomposition,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '10), pp. 1269–1276, June 2010. View at Publisher · View at Google Scholar · View at Scopus
  11. K. Zhang, Q. Liu, Y. Wu, and M.-H. Yang, “Robust visual tracking via convolutional networks without training,” IEEE Transactions on Image Processing, vol. 25, no. 4, pp. 1779–1792, 2016. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  12. H. Nam and B. Han, “Learning multi-domain convolutional neural networks for visual tracking,” in Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR '16), pp. 4293–4302, July 2016. View at Scopus
  13. L. J. Wang, W. L. Ouyang, X. G. Wang, and H. C. Lu, “Visual tracking with fully convolutional networks,” in Proceedings of the IEEE International Conference on Computer Vision (ICCV '15), pp. 3119–3127, Santiago, Chile, December 2015. View at Publisher · View at Google Scholar
  14. C. Ma, J. B. Huang, X. K. Yang, and M. H. Yang, “Hierarchical convolutional features for visual tracking,” in Proceedings of the IEEE International Conference on Computer Vision (ICCV '15), pp. 3074–3082, Santiago, Chile, December 2015. View at Publisher · View at Google Scholar
  15. H. Li, Y. Li, and F. Porikli, “DeepTrack: learning discriminative feature representations online for robust visual tracking,” IEEE Transactions on Image Processing, vol. 25, no. 4, pp. 1834–1848, 2016. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  16. D. Comaniciu, V. Ramesh, and P. Meer, “Real-time tracking of non-rigid objects using mean shift,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '00), pp. 142–149, Hilton Head Island, SC, USA, June 2000. View at Scopus
  17. X. Ben, P. Zhang, W. Meng et al., “On the distance metric learning between cross-domain gaits,” Neurocomputing, vol. 208, pp. 153–164, 2016. View at Publisher · View at Google Scholar · View at Scopus
  18. D. Held, S. Thrun, and S. Savarese, “Learning to track at 100 FPS with deep regression networks,” in European Conference on Computer Vision, vol. 9905, pp. 749–765, Springer International Publishin, 2016. View at Publisher · View at Google Scholar · View at Scopus
  19. H. Zaimaga and M. Lambert, “Soft shrinkage thresholding algorithm for nonlinear microwave imaging,” Journal of Physics: Conference Series, vol. 756, no. 1, Article ID 012011, 2016. View at Publisher · View at Google Scholar · View at Scopus
  20. T. Zhang, B. Ghanem, S. Liu, and N. Ahuja, “Robust visual tracking via multi-task sparse learning,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '12), pp. 2042–2049, Providence, RI, USA, June 2012. View at Publisher · View at Google Scholar · View at Scopus
  21. J. Kwon and K. M. Lee, “Tracking by sampling trackers,” in Proceedings of the 2011 IEEE International Conference on Computer Vision (ICCV '11), pp. 1195–1202, November 2011. View at Publisher · View at Google Scholar · View at Scopus
  22. P. Pérez, C. Hue, J. Vermaak, and M. Gangnet, “Color-based probabilistic tracking,” IEEE Conference Computer Vision Pattern Recognition, pp. 661–675, 2002. View at Publisher · View at Google Scholar
  23. Y. Wu, J. Lim, and M.-H. Yang, “Online object tracking: a benchmark,” in Proceedings of the 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR '13), pp. 2411–2418, Portland, Ore, USA, June 2013. View at Publisher · View at Google Scholar · View at Scopus
  24. W. Chen, K. Zhang, and Q. Liu, “Robust visual tracking via patch based kernel correlation filters with adaptive multiple feature ensemble,” Neurocomputing, vol. 214, pp. 607–617, 2016. View at Publisher · View at Google Scholar · View at Scopus