{"title":"Multi-View Auto-Calibration Method Based on Human Pose Estimation","authors":"Lingling Chen, Zhuo Gong, Lifeng Li, Jian Yin","doi":"10.1109/ICRCV55858.2022.9953175","DOIUrl":null,"url":null,"abstract":"This paper contributes a novel automatic calibration method of a multi-camera system based on human joints. The main difficulty of this problem is the lack of enough known world coordinate points and corresponding two-dimensional image points. Most previous methods address this difficulty by using customized calibration tools, which is tedious due to a lot of manual intervention. In this work, we use human joints as the corresponding points between cameras to deal with this problem. In addition, the proposed method does not need a customized calibration tool, but only requires a person to walk in the calibrated scene, which can reduce the calibration cost greatly. Moreover, the experimental results of binocular and four-camera system indicate that the proposed method outperforms the state of-the-art methods in the case of small public market for both binocular cameras and multi-camera cameras.","PeriodicalId":399667,"journal":{"name":"2022 4th International Conference on Robotics and Computer Vision (ICRCV)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th International Conference on Robotics and Computer Vision (ICRCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRCV55858.2022.9953175","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper contributes a novel automatic calibration method of a multi-camera system based on human joints. The main difficulty of this problem is the lack of enough known world coordinate points and corresponding two-dimensional image points. Most previous methods address this difficulty by using customized calibration tools, which is tedious due to a lot of manual intervention. In this work, we use human joints as the corresponding points between cameras to deal with this problem. In addition, the proposed method does not need a customized calibration tool, but only requires a person to walk in the calibrated scene, which can reduce the calibration cost greatly. Moreover, the experimental results of binocular and four-camera system indicate that the proposed method outperforms the state of-the-art methods in the case of small public market for both binocular cameras and multi-camera cameras.