{"title":"Semantic-Feature-Based Object Recognition by Using Internet Data Mining","authors":"Jing Xu, S. Okada, K. Nitta","doi":"10.1109/WI-IAT.2012.145","DOIUrl":null,"url":null,"abstract":"We consider a problem of automated object description and clustering. Because traditional image-processing-based object recognition algorithms can only cluster objects in image-base, we propose a method to describe an object in human language and group similar objects together in text-processing way. This paper describes a system that recognizes objects with text labels printed on the surface of objects themselves or their packing cases. By analyzing them, objects could be described in English words, and then be clustered into corresponding groups.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI-IAT.2012.145","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We consider a problem of automated object description and clustering. Because traditional image-processing-based object recognition algorithms can only cluster objects in image-base, we propose a method to describe an object in human language and group similar objects together in text-processing way. This paper describes a system that recognizes objects with text labels printed on the surface of objects themselves or their packing cases. By analyzing them, objects could be described in English words, and then be clustered into corresponding groups.