Leslie Guillaume, V. Aubergé, Romain Magnani, Frédéric Aman, Cecile Cottier, Y. Sasa, Christian Wolf, Florian Nebout, N. Neverova, Nicolas Bonnefond, Amaury Nègre, Liliya Tsvetanova, Maxence Girard-Rivier
{"title":"HRI in an ecological dynamic experiment: The GEE corpus based approach for the Emox robot","authors":"Leslie Guillaume, V. Aubergé, Romain Magnani, Frédéric Aman, Cecile Cottier, Y. Sasa, Christian Wolf, Florian Nebout, N. Neverova, Nicolas Bonnefond, Amaury Nègre, Liliya Tsvetanova, Maxence Girard-Rivier","doi":"10.1109/ARSO.2015.7428207","DOIUrl":null,"url":null,"abstract":"As part of a human-robot interaction project, the gestural modality is one of many ways to communicate. In order to develop a relevant gesture recognition system associated to a smart home butler robot, our methodology is based on an IQ game-like Wizard of Oz experiment to collect spontaneous and implicitly produced gestures in an ecological context where the robot is the referee. These gestures are compared with explicitly produced gestures to determine a relevant ontology of gestures. This preliminary qualitative analysis will be the base to build a big data corpus in order to optimize acceptance of the gesture dictionary in coherence with the “socio-affective glue” dynamics.","PeriodicalId":211781,"journal":{"name":"2015 IEEE International Workshop on Advanced Robotics and its Social Impacts (ARSO)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Workshop on Advanced Robotics and its Social Impacts (ARSO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARSO.2015.7428207","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
As part of a human-robot interaction project, the gestural modality is one of many ways to communicate. In order to develop a relevant gesture recognition system associated to a smart home butler robot, our methodology is based on an IQ game-like Wizard of Oz experiment to collect spontaneous and implicitly produced gestures in an ecological context where the robot is the referee. These gestures are compared with explicitly produced gestures to determine a relevant ontology of gestures. This preliminary qualitative analysis will be the base to build a big data corpus in order to optimize acceptance of the gesture dictionary in coherence with the “socio-affective glue” dynamics.