RGB-D Visual Odometry Algorithm Based on Improved ORB for Indoor Environments

Abstract

本文提出一种结合四叉树进行特征信息提取的算法以提高位姿估计的精度。

Introduction

文中提出的一种通过四叉树改进的特征提取方案结合ICP进行位姿估计,之后通过关键帧的选取实现高精度的位姿估计。
RGB-D Visual Odometry Algorithm Based on Improved ORB for Indoor Environments

System Introduction

A.Extract feature points
RGB-D Visual Odometry Algorithm Based on Improved ORB for Indoor Environments

B.Match Feature Points
构建二进制向量描述符进行特征信息的匹配。
C.Camera pose optimization
最小化重投影误差信息获得最优的位姿信息。
D.Key Frame Selection Strategy
针对关键帧的选取,有足够的差异即可作为关键帧。

Experimental Results and Analysis

RGB-D Visual Odometry Algorithm Based on Improved ORB for Indoor EnvironmentsRGB-D Visual Odometry Algorithm Based on Improved ORB for Indoor EnvironmentsRGB-D Visual Odometry Algorithm Based on Improved ORB for Indoor Environments

Conclusion and Future work

这篇文章狗屁不是,公式有错,理论全抄。

Acknowledgement

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