Title
REAL TIME EMBBEDED RGB-D SLAM USING CNNS FOR DEPTH ESTIMATION AND FEATURE EXTRACTION
Author
Marcos Renato Rocha Hernández
Contributor
Gerardo Flores (Thesis Adviser)
Access level
Open Access
Subjects
SLAM - (AUTOR) Inteligencia Artificial - (AUTOR) CNN - (AUTOR) Sistemas embebidos - (AUTOR) Redes neuronales - (AUTOR) Cámara monocular - (AUTOR) INGENIERÍA Y TECNOLOGÍA - (CTI) CIENCIAS TECNOLÓGICAS - (CTI) TECNOLOGÍA DE LOS ORDENADORES - (CTI) INTELIGENCIA ARTIFICIAL - (CTI) INTELIGENCIA ARTIFICIAL - (CTI)
Summary or description
"A robust and efficient Simultaneous Localization and Mapping (SLAM) system is essential for intelligent mobile robots to work in unknown environments. For visual SLAM algorithms, though the theoretical framework has been well established for most aspects, feature extraction and association is still empirically de signed in most cases, and can be vulnerable in complex environments. Also, most of the most robust SLAM algorithms rely on special devices like a stereo camera or depth sensors, which can be expensive and give more complexity to the system, that is why monocular depth estimation is an essential task in the computer vision community. This work shows that feature extraction and depth estimation using a monocular camera with deep convolutional neural networks (CNNs) can be incorporated into a modern SLAM framework. The proposed SLAM system utilizes two CNNs, one to detect keypoints in each im age frame, and to give not only keypoint descriptors, but also a global descriptor of the whole image and the second one to make depth estimations from a single image frame, all using only a monocular camera."
Publish date
March, 2023
Publication type
Master thesis
Publication version
Accepted Version
Information Resource
Format
application/pdf
Language
English
Coverage
León, Guanajuato
Audience
Librarians
Students
Researchers
General public
Citation suggestion
Rocha-Hernández, (2023). "Real time embedded RGB-D slam using CNNS for depth estimation and feature extraction". Tesis de Maestría Interinstitucional en Ciencia y Tecnología. Centro de Investigaciones en Óptica, A.C. León, Guanajuato, México. 52 páginas.
Source repository
REPOSITORIO INSTITUCIONAL DEL CIO
Downloads
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