Journal of Dalian Maritime University >
2018 , Vol. 44 >Issue 4: 121 - 126
DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2018.04.018
An improved ORB_SLAM2 in dynamic scene with semantic segmentation
Received date: 2018-06-19
Revised date: 2018-07-21
Online published: 2018-07-21
In order to improve the accuracy of ORB_SLAM2 in dynamic scene, this paper proposed a method of using semantic segmentation to eliminate the mobile feature points distributed on the human body to improve the accuracy of pose. This method extracted ORB feature points from the input image, semantically segmented the image to obtain the position of the pixels in the image, and then eliminated these feature points distributed on the top of the human body, and estimated the pose using the relatively stable feature points after eliminating. The improved method was tested on the TUM data set, and results show that it can reduce absolute error and relative drift under dynamic environment, which proves that the method is more accurate in pose estimation than the traditional in the dynamic scene.
Key words： semantic segmentation; dynamic scene; pose estimation; ORB_SLAM2
WANG Zhao-dong , GUO Chen . An improved ORB_SLAM2 in dynamic scene with semantic segmentation[J]. Journal of Dalian Maritime University, 2018 , 44(4) : 121 -126 . DOI: 10.16411/j.cnki.issn1006-7736.2018.04.018
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