A Vehicle Tracking Algorithm Based on Mean Shift and C-V Model

The traditional mean shift algorithm uses the tracking window of fixed size,so it is not efficient to track target vehicle,which continuously changes in size.To solve this problem,this paper presented a new vehicle tracking algorithm according to the characteristic of tracked vehicle.The new algorithm is based on the combination of mean shift and C-V model.Firstly,the initial tracking window was obtained with traditional mean shift tracking algorithm,then the tracking window was shifted and reshaped according to the shape information of target vehicle obtained by C-V model.In the tracking process,the shape and color information were both considered.Meanwhile,an improved C-V model was proposed,which used a new level set initialization function.Experiment results have shown that the tracking algorithm improves vehicle tracking accuracy greatly and guarantees real-time tracking.