Background pixel classification for motion detection in video image sequences

Abstract

The main objective in motion detection algorithms for video surveillance applications is to minimize the false alarm probability while maintaining the probability of detection as high as possible. Many motion detection systems fail when the noise in a specific zone is high, increasing the false detection probability, and so the system can not detect motion in these zones. In this paper we present an alternative scheme that tries to solve the mentioned problem using the classification capacity of a neural network.