Abstract
A Long Term Change Detection (CD) Method is presented by definition of a probabilistic model and the integration of two different informative sources. The model is described from a theoretical point of view and its real implementation by means of a bank of shift registers is presented. The algorithm is part of a surveillance system for unattended railway stations: results on a real image sequence confirm its validity.
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References
K. Skifstad, R. Jain, “Illumination Independent Change Detection for Real World Image Sequences”, CVGIP, vol. 46, pp. 387–399, 1989.
T.S. Huang (ed.), Image Sequence Analysis, Springer NY, 1981.
G. Nicchiotti and E. Ottaviani, “Automatic vehicle counting form image sequences”, in Proc. Of Int. Conf. On Time Varying Image Processing and Moving Object Recognition 1993, pp. 410–417.
G.W. Donohoe, D.R. Husg and N. Ahmed, “Change detection for target detection and classification in video sequences”, in Proc. IEEE Conf. Acoustics, Speech and Signal Processing, 1988, pp. 1084–1087.
Z.S. Jain and Y.A. Chau, “Optimum Multisensor Data Fusion for lmage Change Detection”, IEEE Trans. On Systems, Man and Cybernetics, Vol. 25, No. 9, September 1995, pp. 1340–1347.
P. Karmann, A.V. Brandt, “Moving Object Recognition using an adaptive background memory” in Proc. on Int. Conf. On Time Varying and Moving Object Recognition 1990, pp. 289–296.
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© 1997 Springer-Verlag Berlin Heidelberg
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Regazzoni, C.S., Teschioni, A., Stringa, E. (1997). A long term change detection method for surveillance applications. In: Del Bimbo, A. (eds) Image Analysis and Processing. ICIAP 1997. Lecture Notes in Computer Science, vol 1311. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63508-4_159
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DOI: https://doi.org/10.1007/3-540-63508-4_159
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