There is worldwide an increasing concern about security issues. A great deal of efforts have been undertaken in order to provide surveillance systems. This work proposes an automatic method to determine the number of people moving in an area monitored by a video camera, as well as to detect image changes, which are potentially due to illicit attitudes. A typical application is the security of warehouses during the night, on weekends or at any time when people access is allowed but no load movement is admissible. Specifically it focuses on detecting when a person passing by the environment carries any object belonging to the background away or leaves any object in the background, while only people movement is allowed in the area. Besides it estimates the number of people on scene. The method consists of performing four main tasks on video sequences: a) background and foreground separation, b) background estimative dynamic update, c) people location and counting, and d) suspicious attitudes detection. The proposed background and foreground separation and background estimative update algorithms deal with illumination fluctuation and shade effects. People location and counting explores colour information and motion coherence. Solutions meeting these requirements are proposed in the literature, but no one deals with all of them together. The method has been validated by experiments carried out on a prototype and produced encouraging results.