Centroid weighted Kalman filter for visual object tracking

Measurement: Journal of the International Measurement Confederation

Volumn 45, Issue 4, 2012, Pages 650-655

  Fu, Zhaoxia ^a,b   Han, Yan ^a  

^a NORTH UNIVERSITY OF CHINA   (China)

^b Party School of Shanxi Provincial Committee of the CPC   (China)

Author keywords

Background subtraction; Centroid weighted; Kalman filter; Object tracking

Indexed keywords

BACKGROUND SUBTRACTION; BACKGROUND SUBTRACTION METHOD; CENTROID WEIGHTED; MOVING OBJECTS; MOVING TARGETS; OBJECT TRACKING; OBSERVATION DATA; STATE MODELS; TARGET POSITION; VISUAL OBJECT TRACKING; WEIGHTED METHOD;

ALGORITHMS; GAUSSIAN NOISE (ELECTRONIC); UNCERTAINTY ANALYSIS;

KALMAN FILTERS;

EID: 84863418944     PISSN: 02632241     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.measurement.2012.01.004     Document Type: Article

References (20)

1. Y. Bar-Shalom, and T.E. Fortmann Tracking and Data Association 1988 Academic Press New York
2. Naeem Khan, Sajjad Fekri, and Dawei Gu Improvement on state estimation for discrete-time LTI systems with measurement loss Measurement 43 10 2010 1609 1622
3. Ming-Hui Lee, and Tsung-Chien Chen Intelligent fuzzy weighted input estimation method for the forces generated by an operating rotating machine Measurement 44 5 2011 917 926
4. Simon J. Julier, Jeffrey K. Uhlmann, A new extension of the Kalman filter to nonlinear system, in: Proceedings of SPIE, vol. 3068, 1997, pp. 182-193.
5. S. Bogatin, K. Foppe, P. Wasmeier, T.A. Wunderlich, T. Schäfer, and D. Kogoj Evaluation of linear Kalman filter processing geodetic kinematic measurements Measurement 41 5 2008 561 578 (Pubitemid 351458556)
6. J. Ali, and M. Ushaq A consistent and robust Kalman filter design for in-motion alignment of inertial navigation system Measurement 42 4 2009 577 582
7. Dah-Jing Jwo, and Ta-Shun Cho Critical remarks on the linearised and extended Kalman filters with geodetic navigation examples Measurement 43 9 2010 1077 1089
8. L.H. Matthies, T. Kanade, and R. Szeliski Kalman filter-based algorithms for estimating depth from image sequences International Journal of Computer Vision 3 3 1989 209 238
9. P. Li, T. Zhang, and B. Ma Unscented Kalman filter for visual curve tracking Image and Vision Computing 22 2 2004 157 164
10. Shiuh-ku Weng, Chung-ming Kuo, and Shu-kang Tu Video object tracking using adaptive Kalman filter Journal of Visual Communication and Image Representation 17 6 2006 1196 1197
11. B. Karasulu Review and evaluation of well-known methods for moving object detection and tracking in videos Journal of Aeronautics and Space Technologies 4 4 2010 11 22
12. J.C. Nascimento, and J.S. Marques Performance evaluation of object detection algorithms for video surveillance IEEE Transactions on Multimedia 8 4 2006 761 774
13. Y. Benezeth, P.M. Jodoin, B. Emile, H. Laurent, C. Rosenberger, Review and evaluation of commonly-implemented background subtraction algorithms, in: Proceedings of 19th International Conference on Pattern Recognition (ICPR 2008), pp. 1-4.
14. S. Takaba, T. Sekine, B.W. Hwang, A traffic flow measuring system using a solid state sensor, in: Proc. IEE Conf. on Road Traffic Data Collection, London, UK, 1984, pp. 110-114. (Pubitemid 16541760)
15. N. Hoose Impact: an image analysis tool for motorway analysis and surveillance Traffic Engineering and Control 1992 140 147 (Pubitemid 23603803)
16. Ahmed S. Abutaleb Automatic thresholding of gray-level pictures using two-dimensional entropy Computer Vision Graphics and Image Processing 47 1 1989 22 32
17. Yizong Cheng Mean shift, mode seeking, and clustering IEEE Transactions on Pattern Analysis and Machine Intelligence 17 8 1995 790 799
18. D. Comaniciu, and P. Meer Mean shift: a robust approach toward feature space analysis IEEE Transactions on Pattern Analysis and Machine Intelligence 24 5 2002 603 619 (Pubitemid 34550429)
19. C.F. Shan, T.N. Tan, and Y.C. Wei Real-time hand tracking using a mean shift embedded particle filter Pattern Recognition 40 7 2007 1958 1970
20. Z. Li, Q.L. Tang, and N. Sang Improved mean shift algorithm for occlusion pedestrian tracking Electronics Letters 44 10 2008 622 623 (Pubitemid 351643228)