{"title":"3D Sketch Recognition for Interaction in Virtual Environments","authors":"Dominik Rausch, I. Assenmacher, T. Kuhlen","doi":"10.2312/PE/vriphys/vriphys10/115-124","DOIUrl":null,"url":null,"abstract":"We present a comprehensive 3D sketch recognition framework for interaction within Virtual Environments that allows to trigger commands by drawing symbols, which are recognized by a multi-level analysis. It proceeds in three steps: The segmentation partitions each input line into meaningful segments, which are then recognized as a primitive shape, and finally analyzed as a whole sketch by a symbol matching step. The whole framework is configurable over well-defined interfaces, utilizing a fuzzy logic algorithm for primitive shape learning and a textual description language to define compound symbols. It allows an individualized interaction approach that can be used without much training and provides a good balance between abstraction and intuition. We show the real-time applicability of our approach by performance measurements.","PeriodicalId":446363,"journal":{"name":"Workshop on Virtual Reality Interactions and Physical Simulations","volume":"238 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Virtual Reality Interactions and Physical Simulations","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/PE/vriphys/vriphys10/115-124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
We present a comprehensive 3D sketch recognition framework for interaction within Virtual Environments that allows to trigger commands by drawing symbols, which are recognized by a multi-level analysis. It proceeds in three steps: The segmentation partitions each input line into meaningful segments, which are then recognized as a primitive shape, and finally analyzed as a whole sketch by a symbol matching step. The whole framework is configurable over well-defined interfaces, utilizing a fuzzy logic algorithm for primitive shape learning and a textual description language to define compound symbols. It allows an individualized interaction approach that can be used without much training and provides a good balance between abstraction and intuition. We show the real-time applicability of our approach by performance measurements.