{"title":"Sensitivity of image-based and texture-based multi-view coding to model accuracy","authors":"M. Magnor, B. Girod","doi":"10.1109/ICIP.2001.958060","DOIUrl":null,"url":null,"abstract":"Multi-view image coding benefits from knowledge of the depicted scene's 3D geometry. To exploit geometry information for compression, two different approaches can be distinguished. In texture-based coding, images are converted to texture maps prior to compression. In image-based predictive coding, geometry is used for disparity compensation and occlusion detection between images. Coding performance of both approaches depends on the accuracy of the available geometry model. Texture-based and image-based coding are compared with regard to the influence of geometry accuracy on coding efficiency. The results are theoretically explained. Experiments with natural as well as synthetic image sets show that texture-based coding is more sensitive to small geometry inaccuracies than image-based coding. For approximate geometry models, image-based coding performs best, while texture-based coding yields superior coding results if scene geometry is exactly known.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2001.958060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Multi-view image coding benefits from knowledge of the depicted scene's 3D geometry. To exploit geometry information for compression, two different approaches can be distinguished. In texture-based coding, images are converted to texture maps prior to compression. In image-based predictive coding, geometry is used for disparity compensation and occlusion detection between images. Coding performance of both approaches depends on the accuracy of the available geometry model. Texture-based and image-based coding are compared with regard to the influence of geometry accuracy on coding efficiency. The results are theoretically explained. Experiments with natural as well as synthetic image sets show that texture-based coding is more sensitive to small geometry inaccuracies than image-based coding. For approximate geometry models, image-based coding performs best, while texture-based coding yields superior coding results if scene geometry is exactly known.