Real-Time Object Detection in Embedded Video Surveillance Systems
Liliana Lo Presti, Marco La Cascia · 2008
In this paper we report a new method to detect both movingobjects and new stationary objects in video sequences. On the basis of temporal consideration we classify pixels into three classes: background, midground and foreground to distinguish between long-term, medium-term and shortterm changes. The algorithm has been implemented on a hardware platform with limited resources and it could be used in a wider system like a wireless sensor networks. Particular care has been put in realizing the algorithm so that the limited available resources are used in an efficient way. Experiments have been conducted on publicly available datasets and performance measures are reported.