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Online Camera Pose Optimization for the Surround-view System

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Shengjie ZhaoAuthors Info & Claims

MM '19: Proceedings of the 27th ACM International Conference on Multimedia

Pages 383 - 391

https://doi.org/10.1145/3343031.3350885

Published: 15 October 2019 Publication History

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Abstract

Surround-view system is an important information medium for drivers to monitor the driving environment. A typical surround-view system consists of four to six fish-eye cameras arranged around the vehicle. From these camera inputs, a top-down image of the ground around the vehicle, namely the surround-view image can be generated with well calibrated camera poses. Although existing surround-view system solutions can estimate camera poses accurately in off-line environment, how to correct the camera poses' change in online environment is still an open issue. In this paper, we propose a camera pose optimization method for surround-view system in online environment. Our method consists of two models: Ground Model and Ground-Camera Model, both of which correct the camera poses by minimizing photometric errors between ground projections of adjacent cameras. Experiments show that our method can effectively correct the geometric misalignment of the surround-view image caused by camera poses' change. Since our method is highly automated with low requirement of calibration site and manual operation, it has a wide range of applications and is convenient for the end-users. To make the results reproducible, the source code is publicly available at https://cslinzhang.github.io/CamPoseOpt/.

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Cited By

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Hayakawa KNishio HNakagawa YSato T(2025)[Paper] Automatic Calibration of an in-Vehicle Camera based on Structure from MotionITE Transactions on Media Technology and Applications10.3169/mta.13.13613:1(136-146)Online publication date: 2025
https://doi.org/10.3169/mta.13.136
Li JPi JWei PLuo ZYan G(2024)Automatic Multi-Camera Calibration and Refinement Method in Road Scene for Self-Driving CarIEEE Transactions on Intelligent Vehicles10.1109/TIV.2023.33236659:1(2429-2438)Online publication date: Jan-2024
https://doi.org/10.1109/TIV.2023.3323665
Qin LLin CHuang SYang SZhao Y(2024)Camera calibration for the surround-view system: a benchmark and datasetThe Visual Computer10.1007/s00371-024-03275-940:10(7457-7470)Online publication date: 16-Feb-2024
https://doi.org/10.1007/s00371-024-03275-9
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Index Terms

Online Camera Pose Optimization for the Surround-view System
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        Camera calibration

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Online Correction of Camera Poses for the Surround-view System: A Sparse Direct Approach
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Published In

MM '19: Proceedings of the 27th ACM International Conference on Multimedia

October 2019

2794 pages

ISBN:9781450368896

DOI:10.1145/3343031

General Chairs:
Laurent Amsaleg
CNRS-IRISA, France
,
Benoit Huet
EURECOM, France
,
Martha Larson
Radboud University and TU Delft (Netherlands)
,
Program Chairs:
Guillaume Gravier
CNRS-IRISA, France
,
Hayley Hung
Delft University of Technology Netherlands
,
Chong-Wah Ngo
City University of Hong Kong Hong Kong
,
Wei Tsang Ooi
National University of Singapore Singapore

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New York, NY, United States

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Published: 15 October 2019

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MM '19: The 27th ACM International Conference on Multimedia

October 21 - 25, 2019

Nice, France

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MM '19 Paper Acceptance Rate 252 of 936 submissions, 27%;

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Hayakawa KNishio HNakagawa YSato T(2025)[Paper] Automatic Calibration of an in-Vehicle Camera based on Structure from MotionITE Transactions on Media Technology and Applications10.3169/mta.13.13613:1(136-146)Online publication date: 2025
https://doi.org/10.3169/mta.13.136
Li JPi JWei PLuo ZYan G(2024)Automatic Multi-Camera Calibration and Refinement Method in Road Scene for Self-Driving CarIEEE Transactions on Intelligent Vehicles10.1109/TIV.2023.33236659:1(2429-2438)Online publication date: Jan-2024
https://doi.org/10.1109/TIV.2023.3323665
Qin LLin CHuang SYang SZhao Y(2024)Camera calibration for the surround-view system: a benchmark and datasetThe Visual Computer10.1007/s00371-024-03275-940:10(7457-7470)Online publication date: 16-Feb-2024
https://doi.org/10.1007/s00371-024-03275-9
Chen YZhang LShen YZhao BZhou Y(2023)Extrinsic Self-Calibration of the Surround-View System: A Weakly Supervised ApproachIEEE Transactions on Multimedia10.1109/TMM.2022.314488925(1622-1635)Online publication date: 2023
https://doi.org/10.1109/TMM.2022.3144889
Kumar VEising CWitt CYogamani S(2023)Surround-View Fisheye Camera Perception for Automated Driving: Overview, Survey & ChallengesIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.323505724:4(3638-3659)Online publication date: Apr-2023
https://doi.org/10.1109/TITS.2023.3235057
Zhang TZhao NShen YShao XZhang LZhou YShen HZhuang YSmith JYang YCesar PMetze FPrabhakaran B(2021)ROECS: A Robust Semi-direct Pipeline Towards Online Extrinsics Correction of the Surround-view SystemProceedings of the 29th ACM International Conference on Multimedia10.1145/3474085.3475461(3153-3161)Online publication date: 17-Oct-2021
https://dl.acm.org/doi/10.1145/3474085.3475461
Zhang JTao D(2021)Empowering Things With Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of ThingsIEEE Internet of Things Journal10.1109/JIOT.2020.30393598:10(7789-7817)Online publication date: 15-May-2021
https://doi.org/10.1109/JIOT.2020.3039359
Zhang TZhang LShen YMa YZhao SZhou Y(2020)Oecs: Towards Online Extrinsics Correction For The Surround-View System2020 IEEE International Conference on Multimedia and Expo (ICME)10.1109/ICME46284.2020.9102803(1-6)Online publication date: Jul-2020
https://doi.org/10.1109/ICME46284.2020.9102803

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Online Correction of Camera Poses for the Surround-view System: A Sparse Direct Approach

ROECS: A Robust Semi-direct Pipeline Towards Online Extrinsics Correction of the Surround-view System

Camera calibration for the surround-view system: a benchmark and dataset

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