- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Annual Issues
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 352634, 7 pages
Robust Online Object Tracking Based on Feature Grouping and 2DPCA
College of Information & Communication Engineering, Dalian Nationalities University, Dalian 116600, China
Received 20 March 2013; Revised 7 May 2013; Accepted 13 May 2013
Academic Editor: Shangbo Zhou
Copyright © 2013 Ming-Xin Jiang 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.
- A. Yilmaz, O. Javed, and M. Shah, “Object tracking: a survey,” ACM Computing Surveys, vol. 38, no. 4, pp. 229–240, 2006.
- M. X. Jiang, Z. J. Shao, and H. Y. Wang, “Real-time object tracking algorithm with cameras mounted on moving platforms,” International Journal of Image and Graphics, vol. 12, Article ID 1250020, 12 pages, 2012.
- M. X. Kristan, S. Kovačič, A. Leonardis, and J. Perš, “A two-stage dynamic model for visual tracking,” IEEE Transactions on Systems, Man, and Cybernetics B, vol. 40, no. 6, pp. 1505–1520, 2010.
- M. X. Jiang, M. Li, and H. Y. Wang, “A robust combined algorithim of object tracking based on moving object detection,” in Proceedings of the International Conference on Intelligent Control and Information Processing (ICICIP '10), pp. 619–622, Dalian, China, August 2010.
- F. Su, G. Fang, and N. M. Kwok, “Adaptive colour feature identification in image for object tracking,” Mathematical Problems in Engineering, vol. 2012, Article ID 509597, 18 pages, 2012.
- P. Han, J. Du, and M. Fang, “Spatial object tracking using an enhanced mean shift method based on perceptual spatial-space generation model,” Journal of Applied Mathematics, vol. 2013, Article ID 420286, 13 pages, 2013.
- A. M. Sarhan, A. I. Saleh, and R. K. Elsadek, “A reliable event-driven strategy for real-time multiple object tracking using static cameras,” Advances in Multimedia, vol. 2011, Article ID 976463, 20 pages, 2011.
- J. H. Yin, C. Y. Fu, and J. K. Hu, “Using incremental subspace and contour template for object tracking,” Journal of Network and Computer Applications, vol. 35, pp. 1740–1748, 2012.
- S. Avidan, “Support vector tracking,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 8, pp. 1064–1072, 2004.
- O. Williams, A. Blake, and R. Cipolla, “A sparse probabilistic learning algorithm for real-time tracking,” in Proceedings of the 8th IEEE International Conference on Computer Vision, pp. 353–360, October 2003.
- Z. J. Han, J. B. Jiao, B. C. Zhang, Q. X. Ye, and J. Z. Liu, “Visual object tracking via sample-based Adaptive Sparse Representation (AdaSR),” Pattern Recognition, vol. 44, no. 9, pp. 2170–2183, 2011.
- X. Mei and H. Ling, “Robust visual tracking and vehicle classification via sparse representation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 11, pp. 2259–2272, 2011.
- D. Wang, H. Lu, and X. Li, “Two dimensional principal components of natural images and its application,” Neurocomputing, vol. 74, no. 17, pp. 2745–2753, 2011.
- D. A. Ross, J. Lim, R. Lin, and M. Yang, “Incremental learning for robust visual tracking,” International Journal of Computer Vision, vol. 77, no. 1-3, pp. 125–141, 2008.
- Z. Kalal, J. Matas, and K. Mikolajczyk, “P-N learning: bootstrapping binary classifiers by structural constraints,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '10), pp. 49–56, San Francisco, Calif, USA, June 2010.
- 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, San Francisco, Calif, USA, June 2010.
- B. Babenko, S. Belongie, and M. Yang, “Visual tracking with online multiple instance learning,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops '09), pp. 983–990, Miami Beach, Fla, USA, June 2009.
- A. Adam, E. Rivlin, and I. Shimshoni, “Robust fragments-based tracking using the integral histogram,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '06), pp. 798–805, New York, NY, USA, June 2006.