Supervised Object-Specific Distance Estimation from Monocular Images for Autonomous Driving
Accurate distance estimation is a requirement for advanced driver assistance systems (ADAS) to provide drivers with safety-related functions such as adaptive cruise control and collision avoidance. Radars and lidars can be used for providing distance information; however, they are either expensive o...
Main Authors: | Yury Davydov, Wen-Hui Chen, Yu-Chen Lin |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-11-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/22/22/8846 |
Similar Items
-
Synthetic Data Enhancement and Network Compression Technology of Monocular Depth Estimation for Real-Time Autonomous Driving System
by: Woomin Jun, et al.
Published: (2024-06-01) -
SAU-Net: Monocular Depth Estimation Combining Multi-Scale Features and Attention Mechanisms
by: Wei Zhao, et al.
Published: (2023-01-01) -
Train Distance Estimation for Virtual Coupling Based on Monocular Vision
by: Yang Hao, et al.
Published: (2024-02-01) -
Monocular Depth Estimation Using a Laplacian Image Pyramid with Local Planar Guidance Layers
by: Youn-Ho Choi, et al.
Published: (2023-01-01) -
Lightweight Self-Supervised Monocular Depth Estimation Through CNN and Transformer Integration
by: Zhe Wang, et al.
Published: (2024-01-01)