Real-time illumination compensation for face processing in video surveillance

Face processing under illumination variations from video has long been considered as an important and still challenging research issue in video surveillance. In this paper, we propose a real-time pre-processing system to compensate illumination for face processing by using scene lighting modeling. Our contribution lies in the system capability of accommodating multiple local light sources and efficient lighting matching mechanism. Furthermore it can enhance the performance of face processing under both non-standard global and local illumination condition while still maintaining reasonable computing burden for real-time video surveillance. By verifications from face detection results with customized test video clips and public face detection database, the performance of our system outperforms other illumination compensation techniques. This performance improvement in turn will benefit the following face recognition or tracking.