| 參考文獻 |
[1] L. Ling, E. Cheng, and I. S. Burnett, “Eight solutions of the seential matrix for continuous camera motion tracking in video augmented reality,” in Proc. IEEE International Conference on Multimedia and Expo, July 2011.
[2] U. Neumann and S. You, “Integration of region tracking and optical flow for image motion estimation,” in Proc. IEEE International Conference on Image Processing, Oct. 1998.
[3] S.-W. Yang and C.-C. Wang, “Multiple-model RANSAC for ego-motion estimation in highly dynamic environments,” in Proc. IEEE International Conference on Robotics and Automation, May 2009.
[4] I. J. Cox and L. Hingorani, “An efficient implementation of Reld’s multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, No. 2, pp. 138-150, Feb. 1996.
[5] Y. B. Shalom, F. Daum, and J. Huang, “The probabilistic data association filter,” IEEE Transactions on Control Systems Magazine ,Vol. 29, No. 6, pp. 82–100, Dec. 2009.
[6] A. Yilmaz, O. Javed, and M. Shah, “Object tracking: A Survey,” ACM Computing Surveys, Vol. 38, No. 4, pp. 1-45, Dec. 2006.
[7] G. Welch and G. Bishop, “An introduction to the Kalman filter,” Technical Report TR 95-041, University of North Carolina, Department of Computer Science, 1995.
[8] N. Gordon, D. Salmond, and A. Smith, “Novel approach to nonlinear/non-Gaussian Bayesian state estimation,” IEEE Transactions on Radar and Signal Processing, Vol. 140, No. 2, pp. 107-113, Apr. 1993.
[9] K. Nummiaro, E. Koller-Meier, and L. V. Gool, “An adaptive color-based particle filter,” Image and Vision Computing, Vol. 21, No. 1, pp. 99-110, January 2003.
[10] C. R. Blanco, F. Jaureguizar, and N. Garcia, “Bayesian visual surveillance: A model for detecting and tracking a variable number of moving objects,” in Proc. IEEE International Conference on Image Processing, 2011.
[11] M. Meuter, U. Iurgel, S. Park, and A. Kummert, “The un-scented Kalman filter for pedestrian tracking from a moving host,” in Proc. IEEE Symposium on Intelligent Vehicles, June 2008.
[12] C.-C. Lin and W. Wolf, “MCMC-based feature-guided particle filtering for tracking moving objects from a moving platform,” in Proc. IEEE International Conference on Computer Vision, Oct. 2009.
[13] R. Vidal, “Multi-subspace methods for motion segmentation from affine, perspective and central panoramic cameras,” in Proc. IEEE International Conference on Robotics and Automation, pp. 1216-1221, Apr. 2005.
[14] J. Kang, K. Gajera, I. Cohen, and G. Medioni, “Detection and tracking of moving objects from overlapping EO and IR sensors,” in Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2004.
[15] M. D. Breitenstein, F. Reichlin, B. Leibe, E. K. Meier, and L. V. Gool, “Robust tracking-by-detection using a detector confidence particle filter,” in Proc. IEEE International Conference on Computer Vision, Oct. 2009.
[16] M. Ebrahimi, Student Member, and W. W. Mayol-Cuevas, “Adaptive sampling for feature detection, tracking, and recognition on mobile platforms,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 21, No. 10, pp. 1467-1475, Oct. 2011.
[17] C.-M. Huang, Y.-R. Chen, and L.-C. Fu, “Real-time object detection and tracking on a moving camera platform,” in Proc. IEEE ICROS-SICE, Aug. 2005.
[18] J. Kang, I. Cohen, G. Medioni, and C. Yuan, “Detection and tracking of moving objects from a moving platform in presence of strong parallax,” in Proc. IEEE International Conference on Computer Vision, Oct. 2005.
[19] A. Ess, B. Leibe, K. Schindler, and L. V. Gool, “A mobile vision system for robust multi-person tracking,” in Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2008.
[20] J.-Y. Lu, Y.-C. Wei, and C.-W. Tang, “Visual tracking using compensated motion model for mobile cameras,” in Proc. IEEE International Conference on Image Processing, Sep. 2011.
[21] A. Seki and M. Okutomi, “Ego-Motion estimation by matching dewarped road regions using stereo images,” in Proc. IEEE International Conference on Image Processing, Sep. 2006.
[22] B. Jung and G. S. Sukhatme, “Real-time motion tracking from a mobile robot,” International Journal of Social Robotics, Vol. 2, No. 1, pp. 63-78, March 2010.
[23] C. R. Blanco, F. Jaureguizar, L. Salgado, and N. Garcia, “Target detection through motion segmentation and tracking restriction in aerial FLIR images,” in Proc. IEEE International Conference on Image Processing, Oct. 2007.
[24] Z. G. Liu, Y. F. Li, Senior Member and P. Bao, “Stereo-based head tracking with motion compensation model,” in Proc. IEEE International Conference on Robotics and Biomimetics, Oct. 2004.
[25] Y. Jin, “Beyond ICONDENSATION: AICONDENSATION and AFCONDENSATION for visual tracking with low-level and high-level cues,” in Proc. IEEE International Conference on Image Processing, Nov. 2009.
[26] M. Kristan, “A local-motion-based probabilistic model for visual tracking,” The Journal of the Pattern Recognition, Vol. 42, No. 9, pp. 2160-2168, January 2009.
[27] H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool, “SURF: Speeded up robust features,” Computer Vision and Image Understanding, Vol. 110, No. 3, pp. 346–359, 2008.
[28] J. Shi and C. Tomasi, “Good features to track,” in Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 593–600, June 1994.
[29] S. Challa, M. R. Morelande, D. Musicki, and R. L. Evans, “Fundamentals of object tracking”, pp.115-211, Cambridge, UK, 2011.
[30] C. Rasmussen and G. D. Hager, “Probabilistic data association methods for tracking complex visual objects,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 6, pp. 560-575, June 2001.
[31] K. C. Chang and Y. B. Shalom, “Joint probabilistic data association for multitarget tracking with possibly unresolved measurements and maneuvers,” IEEE Transactions on Automatic Control, Vol. 29, No. 7, pp.585-594, July 1984.
[32] I. J. Cox and L. Hingorani, “An efficient implementation of Reld’s multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, No. 2, pp. 138-150, Feb. 1996.
[33] B. Chen and J. K. Tugnait, “Tracking of multiple maneuvering targets in clutter using IMM/JPDA filtering and fixed-lag smoothing,” IEEE Transactions on Automatic Control, Vol. 2, No. 37, pp. 239-249, Feb. 2001.
[34] K. Bai, “Particle filter tracking with mean shift and joint probability data association,” in Proc. IEEE International Conference on Image Analysis and Image Processing, Apr. 2010.
[35] X. Song, B. Wen, J. Cui, H. Zhao, X. Shao, R. Shibasaki, and H.Zha, "A boosted JPDA particle filter for multi-target tracking", in Proc. Asian Workshop on Sensing and Visualization of City-Human Interaction (AWSVCI ), pp.1-4, 2009.
[36] Y. Cai, N. D. Freitas, and J. J. Little, “Robust visual tracking for multiple targets,” in Proc. Europe Conference on Image and Vision Computing, 2006.
[37] M. S. Djouadi Y. Morsly, and D. Berkani, ”JPDA-IMM based particle filter algorithm for tracking highly maneuvering targets,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 43, No. 1, p.p 23-35, Jan. 2007.
[38] N. T. Pham, K. Leman, M. Wong, and F. Gao, “Combining JPDA and particle filter for visual tracking,” in Proc. IEEE International Conference on Multimedia & Expo, 2010.
[39] S. Nikitidis, S. Zafeirious, and I. Pitas. “Camera motion estimation using a novel online vector field model in particle filters,”IEEE Transactions on Circuit and Systems for Video Technology, Vol. 18, No. 8, pp. 1028-1039, Aug. 2008.
[40] J. L. Yang, D. Schonfeld, and M. Mohamed, “Robust video stabilization based on particle filter tracking of projected camera motion,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 19, No. 7, July 2009.
[41] PETs Database, 2001. http://www.hitech-projects.com/euprojects/cantata/datasets_cantata/dataset.html
|
[Endnote RIS 格式]
[相關文章]
[文章引用]
[完整記錄]
[館藏目錄]
[檢視]
plurk
funp
live
udn
HD
myshare
netvibes
friend
youpush
delicious
baidu
Google bookmarks
del.icio.us
hemidemi
facebook
twitter
google
reddit