一种改进ORB特征匹配的半稠密三维重建ORB-SLAM算法

doi:10.16180/j.cnki.issn1007-7820.2021.12.011

Abstract

Abstract:

The goal of visual SLAM technology is to build a more complete map and estimate a more accurate camera pose. To construct a more detailed and complete 3D map, a semi-dense 3D reconstruction ORB-SLAM algorithm with improved ORB feature matching is proposed to realize the construction of a sparse 3D point cloud map of the environment. On the basis of the ORB-SLAM algorithm, a semi-dense mapping thread is added to establish a semi-dense 3D point cloud map. Then, the scale invariance of SURF feature matching algorithm is used to improve ORB feature matching. Simulation experiments in the TUM RGBD datasets reveal that the 3D map established by the improved ORB-SLAM algorithm can more intuitively exhibit the contours of objects in the environment when compared with the ORB-SLAM algorithm, and the feature matching accuracy is increased. Finally, the consistency of the algorithm is verified by experiments in two datasets.

Key words: visual SLAM, semi-dense, three-dimensional reconstruction, ORB feature matching, SURF algorithm, monocular vision, computer vision, image processing

CLC Number:

TP242.6

CHEN Wenyou,ZHANG Wei,SHI Xiaofan,SONG Fang. A Semi-Dense 3D Reconstruction ORB-SLAM Algorithm with Improved ORB Feature Matching[J].Electronic Science and Technology, 2021, 34(12): 62-67.

Figures/Tables 7

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References 16

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序列名称	freiburg1_xyz	freiburg2_xyz
序列时长	30.09	122.74
ORB-SLAM	34.96	180.16
半稠密算法	36.55	191.48
改进ORB-SLAM算法	37.23	194.90

序列名称	freiburg1_xyz	freiburg2_xyz
ORB-SLAM	83.8	86.3
半稠密算法	83.8	86.3
改进ORB-SLAM算法	88.9	91.4

A Semi-Dense 3D Reconstruction ORB-SLAM Algorithm with Improved ORB Feature Matching

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