



@article {2379,
	title = {Efficient approximation of the mahalanobis distance for tracking with the Kalman filter},
	journal = {International Journal of Simulation ModellingInt. J. Simul. Model.},
	volume = {6},
	year = {2007},
	note = {Cited By (since 1996): 3Export Date: 21 November 2012Source: Scopusdoi: 10.2507/IJSIMM06(2)S.03Language of Original Document: EnglishCorrespondence Address: Pinho, R.R.; FEUP - Faculdade de Engenharia da Universidade do Porto, INEGI - Instituto de Engenharia. Mec{\^a}nica e Gest{\~a}o Industrial, LOMe - Lab. de {\'O}ptica e Mec{\r a}nica ExperimentalPortugal; email: rpinho@fe.up.ptReferences: Wren, C., Azarbayejani, A., Darrell, T., Pentland, A., Pfinder: Real-Time Tracking of the Human Body (1997) IEEE Transactions on Pattern Analysis and Machine Intelligence, 19 (7), pp. 780-785;Cucchiara, R., Grana, C., Piccardi, M., Prati, A., Statistic and Knowledge-based Moving Object Detection in Traffic Scenes (2000) Proceedings of the 3rd IEEE Conference on Intelligent Transportation Systems (ITSC2000), , Dearborn, Indiana, USA; 
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Kurita, M., Tsuruoka, S., Yokoi, S., Miyak{\'e}, Y., Handprinted "Kanji" and "Hiragana" character recognition using weighting direction index histograms and quasi-Mahalanobis distance (1983) IEICE Technical Report, , PRL82-79; 
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Sun, F., Omachi, S., Kato, N., Aso, H., Kono, S., Takagi, T., Two-Stage Computational Cost Reduction Algorithm Based on Mahalanobis Distance Approximations (2000) International Conference of Pattern Recognition, , Barcelona, Spain; 
Pinho, R., Tavares, J., Correia, M., Human Movement Tracking and Analysis with Kalman Filtering and Global Optimization Techniques (2005) II International Conference On Computational Bioengineering, , Lisbon, Portugal; 
Welch, G., Bishop, G., An Introduction to Kalman Filter (1995), University of North Carolina at Chapel Hill, Technical Report, TR 95-041Pinho, R., Tavares, J., Correia, M., A Movement Tracking Management Model with Kaiman Filtering, Global Optimization Techniques and Mahalanobis Distance (2005) ICCMSE 2005 International Conf. on Computational Methods in Science and Engineering, , Loutraki, Greece; 
Pinho, R., Tavares, J., Correia, M., An Improved Management Model for Tracking Missing Features in Computer Vision Long Image Sequences (2007) WSEAS Transactions on Information Science and Applications, 4 (1), pp. 196-203; 
Brown, L., Senior, A.W., Tian, Y., Connell, J., Hampapur, A., Shu, C., Merkl, H., Lu, M., Performance Evaluation of Surveillance Systems Under Varying Conditions (2005) IEEE Int. Workshop on Performance Evaluation of Tracking and Surveillance, , Colorado, USA
},
	month = {2007///},
	pages = {84 - 92},
	abstract = {In this paper, we address the problem of tracking feature points along image sequences efficiently. Thus, to estimate the undergoing movement we use an approach based on Kalman filtering, which performs the prediction and correction of the features{\textquoteright} movement in every image frame. Measured data is incorporated by optimizing the global association set built on efficient approximations of the Mahalanobis distance (MD). We analyze the difference between the usage in the tracking results of the original MD formulation and its more efficient approximation, as well as the related computational costs. Experimental results which validate our approach are presented.},
	keywords = {Computational vision, Data association, Kalman filter, Mahalanobis distance, Tracking},
	isbn = {17264529 (ISSN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-34250711808\&partnerID=40\&md5=1c5bde5729463ffbefb5dacc6bacf9fd},
	author = {Pinho, R.R. and Tavares, J.M.R.S. and Correia, M.V.}
}
