Automatic Vehicle Counting from Video for Traffic Flow Analysis

We propose a new video analysis method for counting vehicles, where we use an adaptive bounding box size to detect and track vehicles according to their estimated distance from the camera given the scene-camera geometry. We employ adaptive background subtraction and Kalman filtering for road/vehicle detection and tracking, respectively. Effectiveness of the proposed method for vehicle counting is demonstrated on several video recordings taken at different time periods in a day at one location in the city of Istanbul.