An improved binocular visual odometry algorithm based on the Random Sample Consensus in visual navigation systems
An improved binocular visual odometry algorithm based on the Random Sample Consensus in visual navigation systems
复制标题
视觉导航系统中基于随机样本一致性的改进双目视觉里程计算法
DOI：
10.1108/ir-11-2016-0280
复制
发表时间：
2017-01-01
影响因子：
1.8
通讯作者：
Zhang, Ya
中科院分区：
文献类型：
--
作者：
Sun, Qian;Diao, Ming;Zhang, Ya
目的-本文的目的是提出一种基于随机抽样一致性（RANSAC）的视觉导航system.Design/方法/approach的双目视觉里程算法-作者提出了一种新的双目视觉里程算法的基础上，从加速段测试（FAST）提取器和一种改进的匹配方法的RANSAC的基础上的功能。首先，利用FAST提取器检测特征。其次，利用最近邻和次最近邻的距离比对检测到的特征进行粗匹配。最后，错误匹配的特征对被删除，通过使用RANSAC方法，以减少干扰的错误matchings.Findings -这种新算法的性能进行了检查，由一个实际的实验数据。实验结果表明，该算法不仅提高了特征检测和匹配的鲁棒性，而且显著降低了定位误差。本文还验证了所提出的匹配方法和改进的双目视觉里程算法的可行性和有效性。实用意义-本文提出了一种改进的双目视觉里程算法，已被测试的真实的数据。该算法可用于室外车辆导航。独创性/价值-提出了一种基于FAST提取器和RANSAC方法的双目视觉里程计算法，以提高定位精度和鲁棒性。实验结果验证了该视觉里程计算法的有效性。
Purpose - The purpose of this paper is to propose a binocular visual odometry algorithm based on the Random Sample Consensus (RANSAC) in visual navigation systems.Design/methodology/approach - The authors propose a novel binocular visual odometry algorithm based on features from accelerated segment test (FAST) extractor and an improved matching method based on the RANSAC. Firstly, features are detected by utilizing the FAST extractor. Secondly, the detected features are roughly matched by utilizing the distance ration of the nearest neighbor and the second nearest neighbor. Finally, wrong matched feature pairs are removed by using the RANSAC method to reduce the interference of error matchings.Findings -The performance of this new algorithm has been examined by an actual experiment data. The results shown that not only the robustness of feature detection and matching can be enhanced but also the positioning error can be significantly reduced by utilizing this novel binocular visual odometry algorithm. The feasibility and effectiveness of the proposed matching method and the improved binocular visual odometry algorithm were also verified in this paper.Practical implications - This paper presents an improved binocular visual odometry algorithm which has been tested by real data. This algorithm can be used for outdoor vehicle navigation.Originality/value - A binocular visual odometer algorithm based on FAST extractor and RANSAC methods is proposed to improve the positioning accuracy and robustness. Experiment results have verified the effectiveness of the present visual odometer algorithm.