激光与光电子学进展, 2021, 58 (6): 0611001, 网络出版: 2021-03-06   

面向动态场景的语义视觉里程计 下载: 771次

Semantic-Based Visual Odometry Towards Dynamic Scenes
作者单位
贵州大学大数据与信息工程学院, 贵州 贵阳 550025
摘要
针对传统视觉同时定位与地图构建(vSLAM)相机跟踪模块在动态环境中无法精确定位的问题,提出一种基于语义的视觉里程计。首先,在利用金字塔Lucas-Kanade 光流追踪匹配帧间特征点的同时,对图像进行像素级的语义分割。然后,将语义信息与几何特征紧密结合用以准确地剔除图像中的外点,使得位姿估计和建图仅依靠图像中值得信赖的静态特征点。最后,提出了一种多尺度的随机抽样一致(RANSAC)方案,对匹配点进行步进采样,每步使用不同的尺度因子,在降低外点检测时间的同时,提高了外点检测的鲁棒性。在TUM数据集上的实验结果表明,在高动态序列中,相比于ORB-SLAM2,本文方案的绝对轨迹误差和相对位姿误差改善了90%以上,而相比于同类型的DS-SLAM,本文方案在降低外点检测时间30%~40%的情况下,提升了位姿估计的鲁棒性。
Abstract
To deal with the problem that the camera tracking module of traditional visual simultaneous localization and mapping (vSLAM) can''t make pose estimation accurately, a semantic-based visual odometry is proposed. First, while using pyramid Lucas-Kanade optical flow to track and match the inter-frame feature points, the frame is pixel-wisely segmented. Then, the semantic information and geometric features are combined closely to accurately remove the outliers in the frame, thus the pose estimation and mapping can rely only on the trusted static feature points in the frame. Finally, a multi-scale random sample consensus (RANSAC) scheme is proposed. The matching points are sampled step by step, and different scale threshold are used for each step, which can reduce the detection time and improve the robustness of outliers simultaneously. Experimental results on the TUM data set show that, compared with ORB-SLAM2, the absolute trajectory error and relative pose error of the proposed system are improved by more than 90% in the high dynamic sequence. And the proposed scheme reduced the detection time by 30%-40% while the robustness of pose estimation is improved when compared with similar DS-SLAM.

卢金, 刘宇红, 张荣芬. 面向动态场景的语义视觉里程计[J]. 激光与光电子学进展, 2021, 58(6): 0611001. Lu Jin, Liu Yuhong, Zhang Rongfen. Semantic-Based Visual Odometry Towards Dynamic Scenes[J]. Laser & Optoelectronics Progress, 2021, 58(6): 0611001.

本文已被 5 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!