Real-time tracking via on-line boosting
作者： H. Grabner , M. Grabner , H. Bischof
DOI: 10.5244/C.20.6
关键词: Boosting (machine learning) 、 Tracking system 、 Artificial intelligence 、 Computer vision 、 Compressive tracking 、 Real time tracking 、 Computer science
摘要:
bmva.org
elsevier.com参考文章(26)
Gary R. Bradski, Computer Vision Face Tracking For Use in a Perceptual User Interface ,(1998)
D. Comaniciu, P. Meer, Mean shift analysis and applications international conference on computer vision. ,vol. 2, pp. 1197- 1203 ,(1999) , 10.1109/ICCV.1999.790416
Paul Viola, Michael J. Jones, Daniel Snow, Detecting Pedestrians Using Patterns of Motion and Appearance international conference on computer vision. ,vol. 63, pp. 734- 741 ,(2003) , 10.1007/S11263-005-6644-8
A.D. Jepson, D.J. Fleet, T.R. El-Maraghi, Robust online appearance models for visual tracking computer vision and pattern recognition. ,vol. 1, pp. 415- 422 ,(2001) , 10.1109/CVPR.2001.990505
G.D. Hager, P.N. Belhumeur, Efficient region tracking with parametric models of geometry and illumination IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 20, pp. 1025- 1039 ,(1998) , 10.1109/34.722606
B. Han, L. Davis, On-line density-based appearance modeling for object tracking international conference on computer vision. ,vol. 2, pp. 1492- 1499 ,(2005) , 10.1109/ICCV.2005.181
Ruei-sung Lin, Ming-Hsuan Yang, Jongwoo Lim, David A. Ross, Incremental Learning for Visual Tracking neural information processing systems. ,vol. 17, pp. 793- 800 ,(2004)
A. Elgammal, R. Duraiswami, L.S. Davis, Probabilistic tracking in joint feature-spatial spaces computer vision and pattern recognition. ,vol. 1, pp. 781- 788 ,(2003) , 10.1109/CVPR.2003.1211432
Jianyu Wang, Xilin Chen, Wen Gao, Online selecting discriminative tracking features using particle filter computer vision and pattern recognition. ,vol. 2, pp. 1037- 1042 ,(2005) , 10.1109/CVPR.2005.262
K. Levi, Y. Weiss, Learning object detection from a small number of examples: the importance of good features Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.. ,vol. 2, pp. 53- 60 ,(2004) , 10.1109/CVPR.2004.1315144