{"title":"MirAIProjection","authors":"Kosuke Maeda, Hideki Koike","doi":"10.1145/3399715.3399839","DOIUrl":null,"url":null,"abstract":"Allowing projections on moving objects is associated with a problem that a projection might shift due to the delay between tracking and projection. In the present paper, we proposed a new prediction model based on deep neural networks that can be used to predict both pose and position of the target object. As a result, we developed a real-time tracking and projection system named\"MirAIProjection that employs motion-capture cameras and common projectors. We conducted several experiments to evaluate the effectiveness of the proposed system and demonstrated that the proposed system could reduce the slipping and increase the accuracy and robustness of the projection.","PeriodicalId":149902,"journal":{"name":"Proceedings of the International Conference on Advanced Visual Interfaces","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MirAIProjection\",\"authors\":\"Kosuke Maeda, Hideki Koike\",\"doi\":\"10.1145/3399715.3399839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Allowing projections on moving objects is associated with a problem that a projection might shift due to the delay between tracking and projection. In the present paper, we proposed a new prediction model based on deep neural networks that can be used to predict both pose and position of the target object. As a result, we developed a real-time tracking and projection system named\\\"MirAIProjection that employs motion-capture cameras and common projectors. We conducted several experiments to evaluate the effectiveness of the proposed system and demonstrated that the proposed system could reduce the slipping and increase the accuracy and robustness of the projection.\",\"PeriodicalId\":149902,\"journal\":{\"name\":\"Proceedings of the International Conference on Advanced Visual Interfaces\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Conference on Advanced Visual Interfaces\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3399715.3399839\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Advanced Visual Interfaces","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3399715.3399839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Allowing projections on moving objects is associated with a problem that a projection might shift due to the delay between tracking and projection. In the present paper, we proposed a new prediction model based on deep neural networks that can be used to predict both pose and position of the target object. As a result, we developed a real-time tracking and projection system named"MirAIProjection that employs motion-capture cameras and common projectors. We conducted several experiments to evaluate the effectiveness of the proposed system and demonstrated that the proposed system could reduce the slipping and increase the accuracy and robustness of the projection.