A novel avm calibration method using unaligned square calibration boards

Jung Hyun Lee, Dong Wook Lee

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

An around view monitoring (AVM) system acquires the front, rear, left, and right-side information of a vehicle using four cameras and transforms the four images into one image coordinate system to monitor around the vehicle with one image. Conventional AVM calibration uti-lizes the maximum likelihood estimation (MLE) to determine the parameters that can transform the captured four images into one AVM image. The MLE requires reference data of the image coordinate system and the world coordinate system to estimate these parameters. In conventional AVM calibration, many aligned calibration boards are placed around the vehicle and are measured to extract the reference sample data. However, accurately placing and measuring the calibration boards around a vehicle is an exhaustive procedure. To remediate this problem, we propose a novel AVM calibration method that requires only four randomly placed calibration boards by estimating the location of each calibration board. First, we define the AVM errors and determine the parameters that minimize the error in estimating the location. We then evaluate the accuracy of the proposed method through experiments using a real-sized vehicle and an electric vehicle for chil-dren to show that the proposed method can generate an AVM image similar to the conventional AVM calibration method regardless of a vehicle’s size.

Original languageEnglish
Article number2265
JournalSensors
Volume21
Issue number7
DOIs
StatePublished - 1 Apr 2021

Keywords

  • Around view monitoring system
  • Automatic camera calibration
  • Vision-based advanced driver assistance systems

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