A video-based indoor occupant detection and localization algorithm for smart buildings

Abstract

In buildings, a practical sensing system to collect occupant location information has great importance in improving occupants' comfort and utilizing energy more efficiently by optimizing control strategies of lighting, HVAC devices and elevators. We implement a practical algorithm for occupant detection in use of existing video camera hardware. In our system, we present a novel blob segmentation method based on rule and propose a fast template-based head detection algorithm that matches directly on gradient maps other than edge maps. The accuracy is improved and can satisfy the need of the control system in smart buildings. The speed is about twice as fast as traditional algorithms. © 2009 Springer Berlin Heidelberg.