Automatic threshold selection for automated visual surveillance

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.