Automatic threshold selection for automated visual surveillance

被引：3

作者：

Çelik, T ^{[1
]}

Kabakli, T ^{[1
]}

Uyguroglu, M ^{[1
]}

Özkaramanli, H ^{[1
]}

Demirel, H ^{[1
]}

机构：

[1] Dogu Akdeniz Univ Gazimagusa, Ileri Teknol Arastirma & Gelistirme Enstitusu, KKTC, Gazimagusa, Turkey

来源：

PROCEEDINGS OF THE IEEE 12TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE | 2004年

关键词：

D O I：

10.1109/SIU.2004.1338568

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Automated Visual surveillance systems mostly depend upon effective background subtraction technique. Most of the background subtraction techniques mainly suffer from parameter updates for threshold selection. Here a new threshold selection technique which is found while system trains to learn background, is proposed.

引用

页码：478 / 480

页数：3

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