{"title":"Object State Recognition for Automatic AR-Based Maintenance Guidance","authors":"P. Dvorák, Radovan Josth, Elisabetta Delponte","doi":"10.1109/CVPRW.2017.164","DOIUrl":null,"url":null,"abstract":"This paper describes a component of an Augmented Reality (AR) based system focused on supporting workers in manufacturing and maintenance industry. Particularly, it describes a component responsible for verification of performed steps. Correct handling is crucial in both manufacturing and maintenance industries and deviations may cause problems in later stages of the production and assembly. The primary aim of such support systems is making the training of new employees faster and more efficient and reducing the error rate. We present a method for automatically recognizing an object's state with the objective of verifying a set of tasks performed by a user. The novelty of our approach is that the system can automatically recognize the state of the object and provide immediate feedback to the operator using an AR visualization enabling fully automatic step-by-step instructions.","PeriodicalId":6668,"journal":{"name":"2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","volume":"6 2 1","pages":"1244-1250"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPRW.2017.164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper describes a component of an Augmented Reality (AR) based system focused on supporting workers in manufacturing and maintenance industry. Particularly, it describes a component responsible for verification of performed steps. Correct handling is crucial in both manufacturing and maintenance industries and deviations may cause problems in later stages of the production and assembly. The primary aim of such support systems is making the training of new employees faster and more efficient and reducing the error rate. We present a method for automatically recognizing an object's state with the objective of verifying a set of tasks performed by a user. The novelty of our approach is that the system can automatically recognize the state of the object and provide immediate feedback to the operator using an AR visualization enabling fully automatic step-by-step instructions.