Illumination change compensation techniques to improve kinematic tracking

Illumination changes present challenging problems to video surveillance algorithms tasked with identifying and tracking objects. Illumination changes can drastically alter the appearance of a scene, causing truly salient features to be lost amid otherwise stable background. We describe an illumination change compensation method that identifies large, stable, chromatically distinct background features-called BigBackground regions - which are used as calibration anchors for scene correction. The benefits of this method are demonstrated for a computationally low-cost kinematic tracking application as it attempts to track objects during illumination changes. The BigBackground-based method is compared with other compensation techniques, and is found to successfully track 60% to 80% more objects during illumination changes. Video sequences of pedestrian and vehicular traffic are used for evaluation.