Robust Dense Visual Odometry with boundary pixel suppression

2016 ◽  
Author(s):  
Yijia He ◽  
Yue Guo ◽  
Aixue Ye ◽  
Feng Wen ◽  
Kui Yuan
Keyword(s):  
Visual Odometry ◽  
Boundary Pixel

scholarly journals Event-Based Stereo Visual Odometry

2021 ◽  
pp. 1-18
Author(s):  
Yi Zhou ◽  
Guillermo Gallego ◽  
Shaojie Shen
Keyword(s):  
Visual Odometry ◽  
Event Based ◽  
Stereo Visual Odometry

scholarly journals Semantic 3D Mapping from Deep Image Segmentation

2021 ◽  
Vol 11 (4) ◽  
pp. 1953
Author(s):  
Francisco Martín ◽  
Fernando González ◽  
José Miguel Guerrero ◽  
Manuel Fernández ◽  
Jonatan Ginés
Keyword(s):  
Point Cloud ◽  
Autonomous Mobile Robots ◽  
Semantic Mapping ◽  
Indoor Environments ◽  
3D Mapping ◽  
Direct Mapping ◽  
Learning Techniques ◽  
3D Camera ◽  
Deep Image ◽  
Boundary Pixel

The perception and identification of visual stimuli from the environment is a fundamental capacity of autonomous mobile robots. Current deep learning techniques make it possible to identify and segment objects of interest in an image. This paper presents a novel algorithm to segment the object’s space from a deep segmentation of an image taken by a 3D camera. The proposed approach solves the boundary pixel problem that appears when a direct mapping from segmented pixels to their correspondence in the point cloud is used. We validate our approach by comparing baseline approaches using real images taken by a 3D camera, showing that our method outperforms their results in terms of accuracy and reliability. As an application of the proposed algorithm, we present a semantic mapping approach for a mobile robot’s indoor environments.

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