{"title":"利用三维段和三维面信息的协同进行对象重建","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":"{\"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}","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}
Object reconstruction using the cooperation of 3D segments and 3D facets information
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.<>