Research On Vehicle Tracking Based On Vibe And Camshift Algorithm

In recent years,with the acceleration of urbanization,people’s requirements for the management level of cities are constantly improving,and expect to be more and more fast and intelligent.Based on this demand,the related technologies of target detection and tracking have become a hot topic.In this context,this paper first introduces several common methods of target detection,and analyzes the characteristics of these methods,and then proposes a method of target detection based on vibe algorithm.In the face of the background change,the method uses the flicker level method to suppress the influence of the background change;Then,the adaptive threshold is constructed by using the color characteristics of the image to improve the speed of target detection;Finally,the image edge feature is combined with the improved vibe algorithm to extract the target and complete the target detection;The experimental results show that the algorithm has good target detection effect.At the same time,the method of target tracking is studied on the basis of target detection.Based on the Meanshift method,an improved continuous adaptive Meanshift(Camshift)locating and tracking method is proposed in this paper.In the traditional Camshift method,the hue component of HSV is used to extract the target features and then track the target.However,our improved method combines the hue and saturation components in HSV space to establish a two-dimensional color feature histogram,and then combines the target texture features to improve the tracking accuracy.At the same time,in order to improve the target occlusion and nonlinear changes in the tracking process,the Gaussian Hermite particle filter is introduced to improve the nonlinear problems in the motion.Then the Kalman filter is used to forecast and update the filtered image to improve the tracking effect.In order to verify the method proposed in this paper,we designed relevant experiments,and through the experiment can show that the algorithm proposed in this paper has a good tracking effect in the process of target tracking,meet the relevant requirements of target tracking.Therefore,this algorithm can be widely used in the field of target tracking.