Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles
In intelligent vehicles, extrinsic camera calibration is preferable to be conducted on a regular basis to deal with unpredictable mechanical changes or variations on weight load distribution. Specifically, high-precision extrinsic parameters between the camera coordinate and the world coordinate are...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-07-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/14/4643 |
id |
doaj-88b2a1918d69413f992b710d6c0c29d1 |
---|---|
record_format |
Article |
spelling |
doaj-88b2a1918d69413f992b710d6c0c29d12021-07-23T14:05:08ZengMDPI AGSensors1424-82202021-07-01214643464310.3390/s21144643Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent VehiclesSang Jun Lee0Jae-Woo Lee1Wonju Lee2Cheolhun Jang3Division of Electronic Engineering, Jeonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju-si 54896, Jeollabuk-do, KoreaSamsung Advanced Institute of Technology (SAIT), 130 Samsung-ro, Yeongtong-gu, Suwon-si 16678, Gyeonggi-do, KoreaSamsung Advanced Institute of Technology (SAIT), 130 Samsung-ro, Yeongtong-gu, Suwon-si 16678, Gyeonggi-do, KoreaSamsung Advanced Institute of Technology (SAIT), 130 Samsung-ro, Yeongtong-gu, Suwon-si 16678, Gyeonggi-do, KoreaIn intelligent vehicles, extrinsic camera calibration is preferable to be conducted on a regular basis to deal with unpredictable mechanical changes or variations on weight load distribution. Specifically, high-precision extrinsic parameters between the camera coordinate and the world coordinate are essential to implement high-level functions in intelligent vehicles such as distance estimation and lane departure warning. However, conventional calibration methods, which solve a Perspective-n-Point problem, require laborious work to measure the positions of 3D points in the world coordinate. To reduce this inconvenience, this paper proposes an automatic camera calibration method based on 3D reconstruction. The main contribution of this paper is a novel reconstruction method to recover 3D points on planes perpendicular to the ground. The proposed method jointly optimizes reprojection errors of image features projected from multiple planar surfaces, and finally, it significantly reduces errors in camera extrinsic parameters. Experiments were conducted in synthetic simulation and real calibration environments to demonstrate the effectiveness of the proposed method.https://www.mdpi.com/1424-8220/21/14/4643computer visionintelligent vehiclesextrinsic camera calibrationstructure from motionconvex optimization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sang Jun Lee Jae-Woo Lee Wonju Lee Cheolhun Jang |
spellingShingle |
Sang Jun Lee Jae-Woo Lee Wonju Lee Cheolhun Jang Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles Sensors computer vision intelligent vehicles extrinsic camera calibration structure from motion convex optimization |
author_facet |
Sang Jun Lee Jae-Woo Lee Wonju Lee Cheolhun Jang |
author_sort |
Sang Jun Lee |
title |
Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles |
title_short |
Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles |
title_full |
Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles |
title_fullStr |
Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles |
title_full_unstemmed |
Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles |
title_sort |
constrained multiple planar reconstruction for automatic camera calibration of intelligent vehicles |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2021-07-01 |
description |
In intelligent vehicles, extrinsic camera calibration is preferable to be conducted on a regular basis to deal with unpredictable mechanical changes or variations on weight load distribution. Specifically, high-precision extrinsic parameters between the camera coordinate and the world coordinate are essential to implement high-level functions in intelligent vehicles such as distance estimation and lane departure warning. However, conventional calibration methods, which solve a Perspective-n-Point problem, require laborious work to measure the positions of 3D points in the world coordinate. To reduce this inconvenience, this paper proposes an automatic camera calibration method based on 3D reconstruction. The main contribution of this paper is a novel reconstruction method to recover 3D points on planes perpendicular to the ground. The proposed method jointly optimizes reprojection errors of image features projected from multiple planar surfaces, and finally, it significantly reduces errors in camera extrinsic parameters. Experiments were conducted in synthetic simulation and real calibration environments to demonstrate the effectiveness of the proposed method. |
topic |
computer vision intelligent vehicles extrinsic camera calibration structure from motion convex optimization |
url |
https://www.mdpi.com/1424-8220/21/14/4643 |
work_keys_str_mv |
AT sangjunlee constrainedmultipleplanarreconstructionforautomaticcameracalibrationofintelligentvehicles AT jaewoolee constrainedmultipleplanarreconstructionforautomaticcameracalibrationofintelligentvehicles AT wonjulee constrainedmultipleplanarreconstructionforautomaticcameracalibrationofintelligentvehicles AT cheolhunjang constrainedmultipleplanarreconstructionforautomaticcameracalibrationofintelligentvehicles |
_version_ |
1721286000947232768 |