{"title":"Object reconstruction using the cooperation of 3D segments and 3D facets information","authors":"Didier Gemmerlé","doi":"10.1109/TAI.1994.346403","DOIUrl":null,"url":null,"abstract":"Given a series of trinocular images of an object, we have developed a method for building 3D Facets and 3D segments model of the object. From each triplet, a partial description of the object, called 3D View, is extracted. From the set of all extracted 3D Facets, a strategy for guiding the object reconstruction, based on a statistical method is developed. A 3D Matching Builder computes matchings between the 3D Primitives of consecutive 3D Views. Guided by the strategy, a Superstructure gathers all the matching informations given by the 3D Matching Builder in a set of equivalence classes. For each equivalence class of Superstructure, a representative is derived. The 3D Primitives model is finally computed merging informations of 3D Facet representatives and 3D Segment representatives. This method implemented in Smalltalk80, has been applied on a series of stereoscopic real images triplets; some results are provided at the end of the paper.<<ETX>>","PeriodicalId":262014,"journal":{"name":"Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1994.346403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Given a series of trinocular images of an object, we have developed a method for building 3D Facets and 3D segments model of the object. From each triplet, a partial description of the object, called 3D View, is extracted. From the set of all extracted 3D Facets, a strategy for guiding the object reconstruction, based on a statistical method is developed. A 3D Matching Builder computes matchings between the 3D Primitives of consecutive 3D Views. Guided by the strategy, a Superstructure gathers all the matching informations given by the 3D Matching Builder in a set of equivalence classes. For each equivalence class of Superstructure, a representative is derived. The 3D Primitives model is finally computed merging informations of 3D Facet representatives and 3D Segment representatives. This method implemented in Smalltalk80, has been applied on a series of stereoscopic real images triplets; some results are provided at the end of the paper.<>