Video object tracking using adaptive Kalman filter

[1]  Ramakant Nevatia,et al.  Tracking multiple humans in complex situations , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Arnold W. M. Smeulders,et al.  Fast occluded object tracking by a robust appearance filter , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  J. L. Roux An Introduction to the Kalman Filter , 2003 .

[4]  Seok-Woo Jang,et al.  2D human body tracking with Structural Kalman filter , 2002, Pattern Recognit..

[5]  Liang-Gee Chen,et al.  Efficient moving object segmentation algorithm using background registration technique , 2002, IEEE Trans. Circuits Syst. Video Technol..

[6]  Patrick Pérez,et al.  Towards Improved Observation Models for Visual Tracking: Selective Adaptation , 2002, ECCV.

[7]  Stephen J. Maybank,et al.  Fusion of Multiple Tracking Algorithms for Robust People Tracking , 2002, ECCV.

[8]  Jenq-Neng Hwang,et al.  Fast and automatic video object segmentation and tracking for content-based applications , 2002, IEEE Trans. Circuits Syst. Video Technol..

[9]  A. Senior Tracking people with probabilistic appearance models , 2002 .

[10]  Roberta Piroddi,et al.  Multiple-Feature Spatiotemporal Segmentation of Moving Sequences using a Rule-based Approach , 2002, BMVC.

[11]  Jong Bae Kim,et al.  A Real-Time Region-Based Motion Segmentation Using Adaptive Thresholding and K-Means Clustering , 2001, Australian Joint Conference on Artificial Intelligence.

[12]  David J. Fleet,et al.  Robust online appearance models for visual tracking , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[13]  George V. Paul,et al.  A realtime object tracking system using a color camera , 2001, Proceedings 30th Applied Imagery Pattern Recognition Workshop (AIPR 2001). Analysis and Understanding of Time Varying Imagery.

[14]  Zoran Duric,et al.  Using histograms to detect and track objects in color video , 2001, Proceedings 30th Applied Imagery Pattern Recognition Workshop (AIPR 2001). Analysis and Understanding of Time Varying Imagery.

[15]  Ying Wu,et al.  A co-inference approach to robust visual tracking , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[16]  Thomas B. Moeslund,et al.  A Survey of Computer Vision-Based Human Motion Capture , 2001, Comput. Vis. Image Underst..

[17]  Yiwei Wang,et al.  Moving object tracking in video , 2000, Proceedings 29th Applied Imagery Pattern Recognition Workshop.

[18]  Chee Sun Won,et al.  Fast object tracking in digital video , 2000, IEEE Trans. Consumer Electron..

[19]  Hyung-Il Choi,et al.  Active models for tracking moving objects , 2000, Pattern Recognit..

[20]  David J. Fleet,et al.  Stochastic Tracking of 3D Human Figures Using 2D Image Motion , 2000, ECCV.

[21]  Hai Tao,et al.  Dynamic layer representation with applications to tracking , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[22]  Yang Song,et al.  Towards detection of human motion , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[23]  Johnson I. Agbinya,et al.  Multi-Object Tracking in Video , 1999, Real Time Imaging.

[24]  Hironobu Fujiyoshi,et al.  Moving target classification and tracking from real-time video , 1998, Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201).

[25]  Volker Rehrmann Object Oriented Motion Estimation in Color Image Sequences , 1998, ECCV.

[26]  A. Murat Tekalp,et al.  Motion segmentation by multistage affine classification , 1997, IEEE Trans. Image Process..

[27]  Vance Faber,et al.  Clustering and the continuous k-means algorithm , 1994 .