Automatic Calibration of an Around View Monitor System Exploiting Lane Markings

This paper proposes a method that automatically calibrates four cameras of an around view monitor (AVM) system in a natural driving situation. The proposed method estimates orientation angles of four cameras composing the AVM system, and assumes that their locations and intrinsic parameters are know...

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Main Authors: Kyoungtaek Choi, Ho Gi Jung, Jae Kyu Suhr
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/18/9/2956
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spelling doaj-e4ff421b7b6a4a44b1a7230df9b488e12020-11-24T22:20:07ZengMDPI AGSensors1424-82202018-09-01189295610.3390/s18092956s18092956Automatic Calibration of an Around View Monitor System Exploiting Lane MarkingsKyoungtaek Choi0Ho Gi Jung1Jae Kyu Suhr2Department of Electronic Engineering, Korea National University of Transportation, 50 Daehak-ro, Chungju-si, Chungbuk 27469, KoreaDepartment of Electronic Engineering, Korea National University of Transportation, 50 Daehak-ro, Chungju-si, Chungbuk 27469, KoreaSchool of Intelligent Mechatronics Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, KoreaThis paper proposes a method that automatically calibrates four cameras of an around view monitor (AVM) system in a natural driving situation. The proposed method estimates orientation angles of four cameras composing the AVM system, and assumes that their locations and intrinsic parameters are known in advance. This method utilizes lane markings because they exist in almost all on-road situations and appear across images of adjacent cameras. It starts by detecting lane markings from images captured by four cameras of the AVM system in a cost-effective manner. False lane markings are rejected by analyzing the statistical properties of the detected lane markings. Once the correct lane markings are sufficiently gathered, this method first calibrates the front and rear cameras, and then calibrates the left and right cameras with the help of the calibration results of the front and rear cameras. This two-step approach is essential because side cameras cannot be fully calibrated by themselves, due to insufficient lane marking information. After this initial calibration, this method collects corresponding lane markings appearing across images of adjacent cameras and simultaneously refines the initial calibration results of four cameras to obtain seamless AVM images. In the case of a long image sequence, this method conducts the camera calibration multiple times, and then selects the medoid as the final result to reduce computational resources and dependency on a specific place. In the experiment, the proposed method was quantitatively and qualitatively evaluated in various real driving situations and showed promising results.http://www.mdpi.com/1424-8220/18/9/2956around view monitor (AVM) systemautomatic calibrationlane markingparking assist systemadvanced driver assistance system (ADAS)
collection DOAJ
language English
format Article
sources DOAJ
author Kyoungtaek Choi
Ho Gi Jung
Jae Kyu Suhr
spellingShingle Kyoungtaek Choi
Ho Gi Jung
Jae Kyu Suhr
Automatic Calibration of an Around View Monitor System Exploiting Lane Markings
Sensors
around view monitor (AVM) system
automatic calibration
lane marking
parking assist system
advanced driver assistance system (ADAS)
author_facet Kyoungtaek Choi
Ho Gi Jung
Jae Kyu Suhr
author_sort Kyoungtaek Choi
title Automatic Calibration of an Around View Monitor System Exploiting Lane Markings
title_short Automatic Calibration of an Around View Monitor System Exploiting Lane Markings
title_full Automatic Calibration of an Around View Monitor System Exploiting Lane Markings
title_fullStr Automatic Calibration of an Around View Monitor System Exploiting Lane Markings
title_full_unstemmed Automatic Calibration of an Around View Monitor System Exploiting Lane Markings
title_sort automatic calibration of an around view monitor system exploiting lane markings
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2018-09-01
description This paper proposes a method that automatically calibrates four cameras of an around view monitor (AVM) system in a natural driving situation. The proposed method estimates orientation angles of four cameras composing the AVM system, and assumes that their locations and intrinsic parameters are known in advance. This method utilizes lane markings because they exist in almost all on-road situations and appear across images of adjacent cameras. It starts by detecting lane markings from images captured by four cameras of the AVM system in a cost-effective manner. False lane markings are rejected by analyzing the statistical properties of the detected lane markings. Once the correct lane markings are sufficiently gathered, this method first calibrates the front and rear cameras, and then calibrates the left and right cameras with the help of the calibration results of the front and rear cameras. This two-step approach is essential because side cameras cannot be fully calibrated by themselves, due to insufficient lane marking information. After this initial calibration, this method collects corresponding lane markings appearing across images of adjacent cameras and simultaneously refines the initial calibration results of four cameras to obtain seamless AVM images. In the case of a long image sequence, this method conducts the camera calibration multiple times, and then selects the medoid as the final result to reduce computational resources and dependency on a specific place. In the experiment, the proposed method was quantitatively and qualitatively evaluated in various real driving situations and showed promising results.
topic around view monitor (AVM) system
automatic calibration
lane marking
parking assist system
advanced driver assistance system (ADAS)
url http://www.mdpi.com/1424-8220/18/9/2956
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