Adaptive Model for Foreground Extraction in Adverse Lighting Conditions

Background elimination models are widely used in motion tracking systems. Our aim is to develop a system that performs reliably under adverse lighting conditions. In particular, this includes indoor scenes lit partly or entirely by diffuse natural light. We present a modified “median value” model in which the detection threshold adapts to global changes in illumination. The responses of several models are compared, demonstrating the effectiveness of the new model.

• Type: Conference
• Year: 2004
• Where: PRICAI
• Authors: Stewart Greenhill, Svetha Venkatesh, Geoff A. W. West
• Keywords: Adverse Lighting Conditions, Artificial Intelligence, Background Elimination Models, Motion Tracking Systems, PRICAI 2004