{"title":"A parallel network for the computation of structure from long-range motion","authors":"R. Laganière, F. Labrosse, P. Cohen","doi":"10.1109/IJCNN.1992.227161","DOIUrl":null,"url":null,"abstract":"The authors propose a parallel architecture for computing the 3-D structure of a moving scene from a long image sequence, using a principle known as the incremental rigidity scheme. At each instant an internal model of the 3-D structure is updated, based upon the observations accumulated until that time. The updating process favors rigid transformations but tolerates a limited deviation from rigidity. This deviation eventually leads the internal model to converge towards the actual 3-D structure of the scene. The main advantage of this architecture is its ability to accurately estimate the 3-D structure of the scene at a low computational cost. Testing has been successfully performed on synthetic data as well as real image sequences.<<ETX>>","PeriodicalId":286849,"journal":{"name":"[Proceedings 1992] IJCNN International Joint Conference on Neural Networks","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings 1992] IJCNN International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1992.227161","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
The authors propose a parallel architecture for computing the 3-D structure of a moving scene from a long image sequence, using a principle known as the incremental rigidity scheme. At each instant an internal model of the 3-D structure is updated, based upon the observations accumulated until that time. The updating process favors rigid transformations but tolerates a limited deviation from rigidity. This deviation eventually leads the internal model to converge towards the actual 3-D structure of the scene. The main advantage of this architecture is its ability to accurately estimate the 3-D structure of the scene at a low computational cost. Testing has been successfully performed on synthetic data as well as real image sequences.<>