【摘要】 针对Kinect相机在未知场景中的路径估计问题,提出了一种基于图优化的视觉里程计算法。通过深度图像的光流匹配筛选出关键帧,并得到关键帧的初始位姿估计;将关键帧的初始位姿估计作为顶点,位姿之间的变换作为边构成一个连通图模型,并通过回环检测在图上增加回环;在连通图模型上利用非线性最小二乘对初始位姿优化,从而得到视觉里程计。实验结果表明:提出的方法在满足实时性的基础上,有效减少了误差,这在以视觉里程计为基础的应用中具有很重要的作用。更多还原

【Abstract】 Aiming at the problem of path estimation of Kinect camera in unknown scene,a visual odometry based on graph optimization is proposed. Key frame is screened out by optical flow matching of depth images,and the initial pose estimation of the key frame is obtained. Initial pose estimation of the key frame is taken as the vertex and the transformation between the poses as side to form a connected graph model. And the loopback is added to the graph by loopback detection. Non-linear least squares is used to optimize the initial pose in the graph model,and the visual odometer is obtained. The experimental results show that the method can reduce the error effectively on the basis of meeting real-time performance,which plays an important role in the application based on visual odometer.更多还原