{"title":"Enabling vision-based services with a cloud robotic system","authors":"Jhih-Yuan Huang, Wei-Po Lee","doi":"10.1109/ACIRS.2016.7556193","DOIUrl":null,"url":null,"abstract":"Today cloud computing technologies have been rapidly advancing and researchers often provide various types of resources on the internet to share with each other. In this work, we present a cloud-based robotic service framework for robots to work on such a distributed platform. Our work includes two important services, face recognition and behavior recognition, to supports vision-based robot tasks. Experiments are conducted to validate the proposed methodology and to evaluate its corresponding performance. The results show that successful recognition can be achieved in the static and dynamic experimental environments.","PeriodicalId":364266,"journal":{"name":"2016 Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACIRS.2016.7556193","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
Today cloud computing technologies have been rapidly advancing and researchers often provide various types of resources on the internet to share with each other. In this work, we present a cloud-based robotic service framework for robots to work on such a distributed platform. Our work includes two important services, face recognition and behavior recognition, to supports vision-based robot tasks. Experiments are conducted to validate the proposed methodology and to evaluate its corresponding performance. The results show that successful recognition can be achieved in the static and dynamic experimental environments.