DocumentCode
3486654
Title
Automatic threshold selection for automated visual surveillance
Author
Çelik, Turgay ; Kabakli, Tarik ; Uyguroklu, M. ; Özkaramanli, Huseyin ; Demirel, Hasan
Author_Institution
Ileri Teknoloji Arastirma ve Gelistirme Enstitusu, Dogu Akdeniz Universitesi, Gazimagusa, Turkey
fYear
2004
fDate
28-30 April 2004
Firstpage
478
Lastpage
480
Abstract
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.
Keywords
learning (artificial intelligence); surveillance; video signal processing; automated visual surveillance; automatic threshold selection; background subtraction technique; parameter updates; training; Parametric statistics; Subtraction techniques; Surveillance;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Communications Applications Conference, 2004. Proceedings of the IEEE 12th
Print_ISBN
0-7803-8318-4
Type
conf
DOI
10.1109/SIU.2004.1338568
Filename
1338568
Link To Document