增强室内视觉里程计实用性的方法*

针对现有视觉里程计在实时性、鲁棒性和准确性之间难以协调统一的问题,提出增强视觉里程计实用性的方法.分别运用基于图形处理器的定向加速分割测试特征和旋转感知的二进制鲁棒基元独立特征以及K最邻近加速提取、匹配图像的特征点.根据Kinect有效的深度量程剔除深度误差较大的特征点.求解相机帧间运动时,首先采用高效n点透视快速求解相机帧间运动参数的估计,然后将其作为Levenberg-Marquedt迭代法的初值,优化相机帧间运动参数.在运动参数解计算过程中,使用随机采样一致排除特征外点的干扰.实验表明,文中措施可以提高相机运动轨迹的解算速度,在室内环境下获得的相机运动轨迹更准确,鲁棒性更强,因此适用于室内机器人导航及定位.

Method of Improving Practicability of Indoor Visual Odometry

Aiming at the controversy of the real-time performance, robustness and accuracy in visual odometry, method of improving practicability of indoor visual odometry is put forward to tackle the problem. The corner features of every image in the sequence are obtained using graphics processing unit based oriented FAST and rotated BRIE algorithm and matched using K Nearest neighbor algorithm to reduce the computation time. According to the measurement range of Kinect, points with high measurement error are rejected. To solve the movement of the camera between two frames, the estimation of movement parameters are firstly obtained with efficient perspective-n-point algorithm. Then, they are used as the initial value of Levenberg-Marquedt algorithm to refine the parameters. Random sample consensus is used to reject outliers during the computation of the camera movement. The experimental results show that the proposed method is effective for the accuracy improvement of the motion trajectory calculation.