Flow mosaicking: Real-time pedestrian counting without scene-specific learning
暂无分享,去创建一个
[1] Roberto Cipolla,et al. Unsupervised Bayesian Detection of Independent Motion in Crowds , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[2] Nikos Paragios,et al. A MRF-based approach for real-time subway monitoring , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[3] Sergio A. Velastin,et al. Crowd monitoring using image processing , 1995 .
[4] Sheng-Fuu Lin,et al. Estimation of number of people in crowded scenes using perspective transformation , 2001, IEEE Trans. Syst. Man Cybern. Part A.
[5] Nuno Vasconcelos,et al. Privacy preserving crowd monitoring: Counting people without people models or tracking , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[6] Berthold K. P. Horn,et al. Determining Optical Flow , 1981, Other Conferences.
[7] E. Adelson,et al. Slow and Smooth: A Bayesian theory for the combination of local motion signals in human vision , 1998 .
[8] Ramakant Nevatia,et al. Self-calibration of a camera from video of a walking human , 2002, Object recognition supported by user interaction for service robots.
[9] W. Eric L. Grimson,et al. Adaptive background mixture models for real-time tracking , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).
[10] Paul A. Viola,et al. Detecting Pedestrians Using Patterns of Motion and Appearance , 2005, International Journal of Computer Vision.
[11] Benjamin Z. Yao,et al. Introduction to a Large-Scale General Purpose Ground Truth Database: Methodology, Annotation Tool and Benchmarks , 2007, EMMCVPR.
[12] Luc Van Gool,et al. Coupled Detection and Trajectory Estimation for Multi-Object Tracking , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[13] Antonio Albiol,et al. Real-time high density people counter using morphological tools , 2001, IEEE Trans. Intell. Transp. Syst..
[14] Visvanathan Ramesh,et al. Fast Crowd Segmentation Using Shape Indexing , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[15] A. Marana,et al. On the efficacy of texture analysis for crowd monitoring , 1998, Proceedings SIBGRAPI'98. International Symposium on Computer Graphics, Image Processing, and Vision (Cat. No.98EX237).
[16] Serge J. Belongie,et al. Counting Crowded Moving Objects , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[17] Tsong-Yi Chen,et al. An Intelligent People-Flow Counting Method for Passing Through a Gate , 2006, 2006 IEEE Conference on Robotics, Automation and Mechatronics.
[18] Tommy W. S. Chow,et al. A neural-based crowd estimation by hybrid global learning algorithm , 1999, IEEE Trans. Syst. Man Cybern. Part B.
[19] Hai Tao,et al. A Viewpoint Invariant Approach for Crowd Counting , 2006, 18th International Conference on Pattern Recognition (ICPR'06).
[20] Ramakant Nevatia,et al. Detection of multiple, partially occluded humans in a single image by Bayesian combination of edgelet part detectors , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[21] Marko Heikkilä,et al. A texture-based method for modeling the background and detecting moving objects , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[22] Jean-Philippe Thiran,et al. Counting Pedestrians in Video Sequences Using Trajectory Clustering , 2006, IEEE Transactions on Circuits and Systems for Video Technology.
[23] Yunde Jia,et al. Spatio-temporal patches for night background modeling by subspace learning , 2008, 2008 19th International Conference on Pattern Recognition.
[24] Gary J. Balas,et al. Optical flow: a curve evolution approach , 1996, IEEE Trans. Image Process..