{"title":"与日常工件的原型交互:通过kinect训练和识别3D对象","authors":"Kexi Liu, Dimosthenis Kaleas, Roger Ruuspakka","doi":"10.1145/2148131.2148182","DOIUrl":null,"url":null,"abstract":"In this paper we explore and prototype the interaction with everyday passive objects. We present an approach for 3D object training and recognition, leveraging Kinect sensors: the Dominant Orientation Templates (DOT) method allows real-time object training and multiple Kinects speed up the training process by learning the object from multiple viewpoints simultaneously with the object background removed. A proof-of-concept usage scenario, 3D real-time Lego building instruction, has been developed based on this approach: the system learns the individual Lego pieces and Lego building steps in advance; the users thus construct the Lego model with 3D visual hints attached to present Lego pieces.","PeriodicalId":440364,"journal":{"name":"Proceedings of the Sixth International Conference on Tangible, Embedded and Embodied Interaction","volume":"650 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Prototyping interaction with everyday artifacts: training and recognizing 3D objects via Kinects\",\"authors\":\"Kexi Liu, Dimosthenis Kaleas, Roger Ruuspakka\",\"doi\":\"10.1145/2148131.2148182\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we explore and prototype the interaction with everyday passive objects. We present an approach for 3D object training and recognition, leveraging Kinect sensors: the Dominant Orientation Templates (DOT) method allows real-time object training and multiple Kinects speed up the training process by learning the object from multiple viewpoints simultaneously with the object background removed. A proof-of-concept usage scenario, 3D real-time Lego building instruction, has been developed based on this approach: the system learns the individual Lego pieces and Lego building steps in advance; the users thus construct the Lego model with 3D visual hints attached to present Lego pieces.\",\"PeriodicalId\":440364,\"journal\":{\"name\":\"Proceedings of the Sixth International Conference on Tangible, Embedded and Embodied Interaction\",\"volume\":\"650 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-02-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Sixth International Conference on Tangible, Embedded and Embodied Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2148131.2148182\",\"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 Sixth International Conference on Tangible, Embedded and Embodied Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2148131.2148182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prototyping interaction with everyday artifacts: training and recognizing 3D objects via Kinects
In this paper we explore and prototype the interaction with everyday passive objects. We present an approach for 3D object training and recognition, leveraging Kinect sensors: the Dominant Orientation Templates (DOT) method allows real-time object training and multiple Kinects speed up the training process by learning the object from multiple viewpoints simultaneously with the object background removed. A proof-of-concept usage scenario, 3D real-time Lego building instruction, has been developed based on this approach: the system learns the individual Lego pieces and Lego building steps in advance; the users thus construct the Lego model with 3D visual hints attached to present Lego pieces.