Moving Objects Tracking and Localization with Binocular Vision Based on Sequential Detection Mechanism

To improve the accuracy of object tracking in a complex environment,a binocular vision moving object tracking method is presented based on sequential detection scheme.The proposed method integrates particle filter,sparse field active contour and CamShift algorithms under sequential detection mechanism.Firstly,color-feature-based particle filter is adopted to estimate optimal tracking window.Then the similarity between object and the tracking windows determines whether sparse field active contour algorithm should be performed,whereafter the similarity between the contour and the object determines whether CamShift should be employed to modify the object contour.At last,object's location is obtained based on binocular disparity information and calibration model,and the disparity confidence interval criteria is introduced to decrease the impact of the noise effectively and enhance the object localization accuracy.Experiments demonstrate that the proposed method can effectively track and locate the moving object in both camera moving and object moving,and it is able to track and locate the object accurately in both target changes in scale,orientation,view and environment illumination changes.