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Monocular Visual Odometry Approach for Trajectory Estimation of a Moving Object Using Ground Plane Geometry

机译:利用地平面几何学进行运动物体轨迹估计的单目视觉里程表法

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Trajectory estimation of a moving object using monocular visual odometry approach is an important research direction in computer vision. The moving object can be a car or a robot or anything which is carrying camera need to be tracked for autonomous navigation. Scale estimation of the translational motion is tedious in monocular visual odometry system. This paper proposes a new trajectory estimation algorithm in which Nister's 5-point algorithm is used as the baseline algorithm. We have adapted the method discussed in [1] for the scale estimation of trajectory with the additional input of camera height. Estimated scale is nothing but the ratio between the known camera height and the estimated camera height. The camera height shall be found by decomposing the Homography matrix. The proposed algorithm is tested with KITTI standard benchmark dataset [2]. Experimental results on KITTI dataset shows significant improvement in the trajectory estimation of moving object.
机译:使用单眼视觉测距法对运动物体进行轨迹估计是计算机视觉的重要研究方向。运动对象可以是汽车或机器人,或者需要跟踪携带相机的任何东西以进行自主导航。在单眼视觉测距系统中,平移运动的比例估计很繁琐。本文提出了一种新的轨迹估计算法,其中将Nister的5点算法用作基线算法。我们已经将[1]中讨论的方法与摄像机高度的额外输入相结合,用于轨迹的比例估计。估计比例不过是已知摄像机高度与估计摄像机高度之间的比率。摄像机高度应通过分解同构矩阵求出。所提出的算法已通过KITTI标准基准数据集进行了测试[2]。在KITTI数据集上的实验结果表明,在移动物体的轨迹估计方面有了显着的改进。

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