{"title":"A camera calibration technique based on planar geometry feature","authors":"A. Chen, B. He","doi":"10.1109/MMVIP.2007.4430736","DOIUrl":null,"url":null,"abstract":"In this paper, a new technique for camera calibration based on planar geometry feature is proposed. It only requires three views from the newly designed planar calibration pattern, which is a square tessellated model plane with the black-and-white alternate square grids, then all the five intrinsic parameters can be recovered linearly. Our calibration method needs; neither any geometric measurements on the model plane, nor any matching information between the model plane and the image plane, and avoids the errors caused by the pick-up of irregular geometry feature from the image. It greatly decreases the system setup costs and simplifies image feature extraction works. Hence the calibration process is easily performed for the user. Experimental results on simulated data and real data show the feasibility of the proposed technique.","PeriodicalId":421396,"journal":{"name":"2007 14th International Conference on Mechatronics and Machine Vision in Practice","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 14th International Conference on Mechatronics and Machine Vision in Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMVIP.2007.4430736","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, a new technique for camera calibration based on planar geometry feature is proposed. It only requires three views from the newly designed planar calibration pattern, which is a square tessellated model plane with the black-and-white alternate square grids, then all the five intrinsic parameters can be recovered linearly. Our calibration method needs; neither any geometric measurements on the model plane, nor any matching information between the model plane and the image plane, and avoids the errors caused by the pick-up of irregular geometry feature from the image. It greatly decreases the system setup costs and simplifies image feature extraction works. Hence the calibration process is easily performed for the user. Experimental results on simulated data and real data show the feasibility of the proposed technique.