计算机工程2018，Vol.44Issue(1)：1-8,8.DOI:10.3969/j.issn.1000-3428.2018.01.001
基于局部与全局优化的双目视觉里程计算法
Binocular Visual Odometry Algorithm Based on Local and Global Optimization
摘要
Abstract
A novel binocular Visual Odometry (VO) algorithm is proposed for real-time precise localization of mobile robots.Firstly,it uses accelerated Scale Invariant Feature Transform (SIFT) operator to extract the image features on the left and right image.The sparse stereo matching is carried out after the extracting.In addition,the method of features tracking is applied between the previous and current image.Thus,the initial pose including rotation and translation matrix can be obtained with the motion estimation method based on the RANSAC strategy.Secondly,the image sequence is divided into key frames and non-key frames.In order to decrease the error of the inter-frame motion estimation,a variable sliding window is applied to optimizing the pose of adjacent key frames locally and nonlinearly.Finally,the closed-loop detection is applied by the method of bag of words.Furthermore,all the poses of key frames in the closed-loop are optimized globally to avoid the error accumulation and the drift of the trajectory.Experimental results show that the proposed algorithm has good real-time performance,while reducing the position pose error and improving the positioning accuracy.关键词
双目视觉里程计/运动估计/局部优化/全局优化/特征匹配Key words
binocular Visual Odometry(VO)/motion estimation/local optimization/global optimization/feature matching分类
信息技术与安全科学引用本文复制引用
杨冬冬,张晓林,李嘉茂..基于局部与全局优化的双目视觉里程计算法[J].计算机工程,2018,44(1):1-8,8.基金项目
国家自然科学基金青年项目(61601448). （61601448）
