Enhancing Around View System for VEHICLES: Lut Correction Via Deep Learning
- Authors
- Park, Joohyun; Choi, Woorim; Lee, Hyeonuk; Lee, Hyojin; Yun, Sangwoo; Paik, Joonki
- Issue Date
- Jan-2024
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- around view; deep learning; feature matching
- Citation
- 2024 International Conference on Electronics, Information, and Communication, ICEIC 2024
- Journal Title
- 2024 International Conference on Electronics, Information, and Communication, ICEIC 2024
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/73330
- DOI
- 10.1109/ICEIC61013.2024.10457280
- ISSN
- 0000-0000
- Abstract
- We present around view system enhanced by deep learning techniques. The around view system is an essential component in autonomous driving and parking systems. Traditional around view systems have been designed using handcrafted algorithms. Moreover, utilizing pre-generated look-up tables (LUTs) has not been effective in reducing errors that occur during driving. We propose an algorithm that leverages deep learning-based methods to correct while driving. By using deep learning for feature matching, we can update the LUT to decrease the errors between different viewpoints. © 2024 IEEE.
- Files in This Item
-
- Appears in
Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.