Daiki Kitayama, Yasufumi Touma, H. Hagiwara, K. Asami, M. Komori
{"title":"3D map construction based on structure from motion using stereo vision","authors":"Daiki Kitayama, Yasufumi Touma, H. Hagiwara, K. Asami, M. Komori","doi":"10.1109/ICIEV.2015.7334018","DOIUrl":null,"url":null,"abstract":"In this paper 3D map construction using stereovision for autonomous mobile robot is presented. Parallax images by the triangulation method is obtained so as to calculate the 3D coordinates at the feature points. In addition, the Structure from Motion method is used so as to estimate the self-position of the camera to integrate the 3D map. In order to generate more accurate 3D map, the stereo vision system must deal with problems such as aperture problem and noise. The construction of the stereo measurement system and the experiment with mitigating the visual problems are conducted. The practical 3D map for the typical corridor environment was generated from the high-speed stereo image processing within 900 ms per scene.","PeriodicalId":367355,"journal":{"name":"2015 International Conference on Informatics, Electronics & Vision (ICIEV)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Informatics, Electronics & Vision (ICIEV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEV.2015.7334018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper 3D map construction using stereovision for autonomous mobile robot is presented. Parallax images by the triangulation method is obtained so as to calculate the 3D coordinates at the feature points. In addition, the Structure from Motion method is used so as to estimate the self-position of the camera to integrate the 3D map. In order to generate more accurate 3D map, the stereo vision system must deal with problems such as aperture problem and noise. The construction of the stereo measurement system and the experiment with mitigating the visual problems are conducted. The practical 3D map for the typical corridor environment was generated from the high-speed stereo image processing within 900 ms per scene.