Vehicle Tracking in Low Hue Contrast Based on CAMShift and Background Subtraction

This paper proposes a method to track vehicle in highway using CAMShift-based method. The Continuously Adaptive Mean Shift (CAMShift) is a well-known algorithm in object tracking. However, the ordinary CAMShift works fairly well only for tracking object that can identify by hue, when the difference between object color and background is large. This is not the case in vehicle tracking. The objective of our proposed method is to be able to track vehicles in highway when the hue contrast is low. We incorporate in CAMShift an adaptive background subtraction to help in object localization when lost tracking occurs. The experimental result illustrates a significant improvement in tracking accuracy.