Towards Visual-Inertial SLAM for Dynamic Environments Using Instance Segmentation and Dense Optical Flow

Towards Visual-Inertial SLAM for Dynamic Environments Using Instance Segmentation and Dense Optical Flow

Dynamic environments pose an open problem for the performance of visual SLAM systems in real-life scenarios. Such environments involve dynamic objects that can cause pose estimation errors. Recently, Deep Learning semantic segmentation networks have been employed to identify potentially moving objec...

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Bibliographic Details
Main Author: Sarmiento Gonzalez, Luis Alejandro
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2021
Subjects:
Semantic SLAM
Stereo Vision
VisualInertial SLAM
Motion likelihood
Stereo disparity
Dense optical flow
Dynamic objects.
Semantisk SLAM
Visual-Inertial SLAM
Sannolikhet för rörelse
Stereoskillnader
Tätt optiskt flöde
Dynamiska objekt.
Computer and Information Sciences
Data- och informationsvetenskap
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-305443

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-305443

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