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Automatic threshold selection for automated visual surveillance

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5 Author(s)
Celik, T. ; Ileri Teknoloji Arastirma ve Gelistirme Enstitusu, Dogu Akdeniz Universitesi, Gazimagusa, Turkey ; Kabakli, T. ; Uyguroklu, M. ; Ozkaramanli, H.
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Automated visual surveillance systems mostly depend on an effective background subtraction technique. Most background subtraction techniques suffer mainly from parameter updates for threshold selection. A new threshold selection technique, which is found while training the system to learn the background, is proposed.

Published in:

Signal Processing and Communications Applications Conference, 2004. Proceedings of the IEEE 12th

Date of Conference:

28-30 April 2004