Results 11 to 20 of about 24,057 (250)

Depth-Adapted CNN for RGB-D Cameras [PDF]

open access: yes, 2021
Conventional 2D Convolutional Neural Networks (CNN) extract features from an input image by applying linear filters. These filters compute the spatial coherence by weighting the photometric information on a fixed neighborhood without taking into account the geometric information. We tackle the problem of improving the classical RGB CNN methods by using
Wu, Zongwei   +3 more
openaire   +3 more sources

PL-GM:RGB-D SLAM With a Novel 2D and 3D Geometric Constraint Model of Point and Line Features

open access: yesIEEE Access, 2021
In the study of RGB-D SLAM (Simultaneous Localization and Mapping), two types of primary visual features, point and line features, have been widely utilized to calculate the camera pose.
Chenyang Zhang
doaj   +1 more source

Visual Odometry for RGB-D Cameras

open access: yesCoRR, 2022
Visual odometry is the process of estimating the position and orientation of a camera by analyzing the images associated to it. This paper develops a quick and accurate approach to visual odometry of a moving RGB-D camera navigating on a static environment.
Afonso Fontes, José Everardo Bessa Maia
openaire   +2 more sources

Survey and Evaluation of RGB-D SLAM

open access: yesIEEE Access, 2021
The traditional visual SLAM systems take the monocular or stereo camera as input sensor, with complex map initialization and map point triangulation steps needed for 3D map reconstruction, which are easy to fail, computationally complex and can cause ...
Shishun Zhang, Longyu Zheng, Wenbing Tao
doaj   +1 more source

TIMA SLAM: Tracking Independently and Mapping Altogether for an Uncalibrated Multi-Camera System

open access: yesSensors, 2021
We present a novel simultaneous localization and mapping (SLAM) system that extends the state-of-the-art ORB-SLAM2 for multi-camera usage without precalibration.
Omer Faruk Ince, Jun-Sik Kim
doaj   +1 more source

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