Jing Qian, Laurent Denoue, Jacob T. Biehl, David A. Shamma
{"title":"用于切换AR中交互线性度的AI","authors":"Jing Qian, Laurent Denoue, Jacob T. Biehl, David A. Shamma","doi":"10.1109/AIVR.2018.00040","DOIUrl":null,"url":null,"abstract":"Interaction in augmented reality (AR) or mixed reality environments is generally classified into two modalities: linear (relative to object) or non-linear (relative to camera). Switching between these modes tailors the AR experience to different scenarios. Such interactions can be arduous in cases when on-board touch interaction is limited or restricted as is often the case in medical or industrial applications that require sterility. To solve this, we present Sound-to-Experience where the modality can be effectively toggled by noise or sound which is detected using a modern Artificial Intelligence deep-network classifier.","PeriodicalId":371868,"journal":{"name":"2018 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"AI for Toggling the Linearity of Interactions in AR\",\"authors\":\"Jing Qian, Laurent Denoue, Jacob T. Biehl, David A. Shamma\",\"doi\":\"10.1109/AIVR.2018.00040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Interaction in augmented reality (AR) or mixed reality environments is generally classified into two modalities: linear (relative to object) or non-linear (relative to camera). Switching between these modes tailors the AR experience to different scenarios. Such interactions can be arduous in cases when on-board touch interaction is limited or restricted as is often the case in medical or industrial applications that require sterility. To solve this, we present Sound-to-Experience where the modality can be effectively toggled by noise or sound which is detected using a modern Artificial Intelligence deep-network classifier.\",\"PeriodicalId\":371868,\"journal\":{\"name\":\"2018 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIVR.2018.00040\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIVR.2018.00040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AI for Toggling the Linearity of Interactions in AR
Interaction in augmented reality (AR) or mixed reality environments is generally classified into two modalities: linear (relative to object) or non-linear (relative to camera). Switching between these modes tailors the AR experience to different scenarios. Such interactions can be arduous in cases when on-board touch interaction is limited or restricted as is often the case in medical or industrial applications that require sterility. To solve this, we present Sound-to-Experience where the modality can be effectively toggled by noise or sound which is detected using a modern Artificial Intelligence deep-network classifier.