CAJ | 학술논문

提出了一种基于最小平方中值定理(LMedS)的立体视觉里程计方法.利用图像中尺度不变的SIFT特征点作为路标,基于KD树的最邻近点搜索算法来实现左右图像对特征点的匹配和前后帧间特征点跟踪.通过特征点的三维重建,基于最小平方中值定理估计出机器人的运动距离和方向信息.实验表明该方法在不同图像间匹配、三维路标跟踪和机器人运动估计中具有很强的鲁棒性.
제출료일충기우최소평방중치정리(LMedS)적입체시각리정계방법.이용도상중척도불변적SIFT특정점작위로표,기우KD수적최린근점수색산법래실현좌우도상대특정점적필배화전후정간특정점근종.통과특정점적삼유중건,기우최소평방중치정리고계출궤기인적운동거리화방향신식.실험표명해방법재불동도상간필배、삼유로표근종화궤기인운동고계중구유흔강적로봉성.
An approach based on least median squares (LMedS) to a stereo-based visual odometry system is presented.Utilizing the scale invariant SITF features in the images as landmarks,the feature matching is implemented with the KD-tree-based nearest search approach to achieve feature matching between stereo images and feature tracking between consecutive frames.Using the 3D reconstruction of the feature,the LMeds method is applied to estimate the information of the robot.The experiments demonstrate the algorithm is robustness in feature matching between different images,the tracking of 3D landmarks and the motion estimation of robot.