{"title":"Simplified depth-based block partitioning and prediction merging in 3D video coding","authors":"Fabian Jäger, M. Wien","doi":"10.1109/VCIP.2014.7051519","DOIUrl":null,"url":null,"abstract":"3D video is an emerging technology that bundles depth information with texture videos to allow for view synthesis applications at the receiver. Depth discontinuities define object boundaries in both, depth maps and the collocated texture video. Therefore, depth segmentation can be utilized for a fine-grained motion field partitioning of the corresponding texture component. In this paper, depth information is used to increase coding efficiency for texture videos by deriving an arbitrarily shaped partitioning. By applying motion compensation to each partition independently and eventually merging the two prediction signals, highly accurate prediction signals can be produced that reduce the remaining texture residual signal significantly. Simulation results show bitrate savings of up to 2.8% for the dependent texture views and up to about 1.0% with respect to the total bitrate.","PeriodicalId":166978,"journal":{"name":"2014 IEEE Visual Communications and Image Processing Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Visual Communications and Image Processing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VCIP.2014.7051519","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
3D video is an emerging technology that bundles depth information with texture videos to allow for view synthesis applications at the receiver. Depth discontinuities define object boundaries in both, depth maps and the collocated texture video. Therefore, depth segmentation can be utilized for a fine-grained motion field partitioning of the corresponding texture component. In this paper, depth information is used to increase coding efficiency for texture videos by deriving an arbitrarily shaped partitioning. By applying motion compensation to each partition independently and eventually merging the two prediction signals, highly accurate prediction signals can be produced that reduce the remaining texture residual signal significantly. Simulation results show bitrate savings of up to 2.8% for the dependent texture views and up to about 1.0% with respect to the total bitrate.