Dynamic Semantic Occupancy Mapping Using 3D Scene Flow and Closed-Form Bayesian Inference

Dynamic Semantic Occupancy Mapping Using 3D Scene Flow and Closed-Form Bayesian Inference

This paper reports on a dynamic semantic mapping framework that incorporates 3D scene flow measurements into a closed-form Bayesian inference model. Existence of dynamic objects in the environment can cause artifacts and traces in current mapping algorithms, leading to an inconsistent map posterior....

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Bibliographic Details
Main Authors: Aishwarya Unnikrishnan, Joey Wilson, Lu Gan, Andrew Capodieci, Paramsothy Jayakumar, Kira Barton, Maani Ghaffari
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Bayesian inference
computer vision
mapping
semantic scene understanding
Online Access:https://ieeexplore.ieee.org/document/9882042/

Internet

https://ieeexplore.ieee.org/document/9882042/

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