To enhance the tracking performance of textureless parts in the augmented reality assembly system,a re-gion-based 3D tracking method was proposed.A new smooth step function was used to optimize the image segmen-tation method based on level-set function,which improved the segmentation effect of contour edges.Then,a pixel foreground and background color posterior probability statistical model was designed to enhance the time consistency between continuous frames and improve the robustness and accuracy against motion blur.Finally,the Gauss-Newton method was used for pose optimization,with its fast convergence and numerical stability ensuring real-time and sta-bility of the algorithm.Experimental results demonstrated that the proposed 3D tracking method could accurately track textureless parts.Meanwhile,the image segmentation and pose estimation exhibit stronger robustness against disturbances such as motion blur or cluttered backgrounds,meeting the requirements of tracking textureless parts in industrial scenarios.
关键词
增强装配/前背景区域/图像分割/姿态估计/三维目标跟踪
Key words
augmented assembly/foreground and background region/image segmentation/pose estimation/3D object tracking
维普
万方数据