Object detection and tracking in time-varying and badly illuminated outdoor environments

Abstract

A real-time method for object detection and tracking in outdoor environments where illumination can be very low and not constant is presented. A hierarchical (two levels) change detection method is employed to detect moving objects in the scene. At the first level, a focus-of-attention stage is applied to individuate image areas containing moving objects; at the second level, each selected image area is inspected at higher accuracy to improve the detection probability and to obtain an accurate binary reconstruction of the object shape. A background updating procedure is used to adapt the background image to the changes in the scene. Then, an extended Kalman filter is applied to track multiple objects entering the scene. Results are reported on real scenarios in the presence of shadows, occlusions, light reflections, and bad environmental conditions. © 1998 Society of Photo-Optical Instrumentation Engineers.