Image-based depth estimation in autonomous driving environment

Depth estimation is one of the critical problems for autonomous vehicles (AVs) in 3D building modeling, SLAM, and localization. One solution is to leverage Radar and LiDAR to capture sparse point clouds, while the hardware is expensive for wide applications. Alternatively, deep learning (DL) network...

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Main Author: Yang, Ziqin
Other Authors: Tay Wee Peng
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/158161
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1581612023-07-07T19:34:56Z Image-based depth estimation in autonomous driving environment Yang, Ziqin Tay Wee Peng School of Electrical and Electronic Engineering wptay@ntu.edu.sg Engineering::Electrical and electronic engineering Depth estimation is one of the critical problems for autonomous vehicles (AVs) in 3D building modeling, SLAM, and localization. One solution is to leverage Radar and LiDAR to capture sparse point clouds, while the hardware is expensive for wide applications. Alternatively, deep learning (DL) networks have accomplished high performance in various vision tasks including image-based depth estimation, where only a camera is needed for image capturing. In this project, we investigate models to estimate depth using pure image information. We also conduct experiments to demonstrate the effectiveness and to evaluate the performance of these investigated models. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-27T07:28:21Z 2022-05-27T07:28:21Z 2022 Final Year Project (FYP) Yang, Z. (2022). Image-based depth estimation in autonomous driving environment. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158161 https://hdl.handle.net/10356/158161 en A3248-211 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Yang, Ziqin
Image-based depth estimation in autonomous driving environment
description Depth estimation is one of the critical problems for autonomous vehicles (AVs) in 3D building modeling, SLAM, and localization. One solution is to leverage Radar and LiDAR to capture sparse point clouds, while the hardware is expensive for wide applications. Alternatively, deep learning (DL) networks have accomplished high performance in various vision tasks including image-based depth estimation, where only a camera is needed for image capturing. In this project, we investigate models to estimate depth using pure image information. We also conduct experiments to demonstrate the effectiveness and to evaluate the performance of these investigated models.
author2 Tay Wee Peng
author_facet Tay Wee Peng
Yang, Ziqin
format Final Year Project
author Yang, Ziqin
author_sort Yang, Ziqin
title Image-based depth estimation in autonomous driving environment
title_short Image-based depth estimation in autonomous driving environment
title_full Image-based depth estimation in autonomous driving environment
title_fullStr Image-based depth estimation in autonomous driving environment
title_full_unstemmed Image-based depth estimation in autonomous driving environment
title_sort image-based depth estimation in autonomous driving environment
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/158161
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