基于图像矩的运动目标3D平动视觉跟踪

IMAGE MOMENTS BASED VISUAL TRACKING OF 3D TRANSLATIONAL MOTION

  • 摘要: 区别于图像的简单几何特征,本文利用图像的全局特征描述子-图像矩特征作为图像特征信息,实现了基于图像的运动目标3D平动的视觉跟踪.针对任务要求,本文选取了一组矩特征用以完成任务.基于所选的矩,本文给出了矩特征变化量与相对位姿变化量之间的关系矩阵,即图像雅可比矩阵,然后利用所推导的图像雅可比矩阵,设计了由图像反馈与目标运动自适应补偿组成的视觉伺服控制器,实现了在未知目标成-深度及摄像机焦距的情况下对运动目标的3D平动跟踪.

     

    Abstract: This paper describes a visual tracking method which uses image moment as image feature for tracking a target that moves in 3D with translational motion. According to the specific tasks, a set of moment is selected as image feature. Then, the moment-based Jacobian is deduced. With the moment-based Jacobian, the visual servoing controller composed of image-based feedback and adaptive motion compensation is designed to track the moving target. In the tracking process, the knowledge of camera focus and depth of object is unnecessary. The simulation results show that using image moment as image feature can avoid the complex feature matching process, and acquire a satisfied tracking accuracy.

     

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