{"title":"基于立体视频源的场景流估计","authors":"Aniket Bera","doi":"10.1145/2007052.2007058","DOIUrl":null,"url":null,"abstract":"There are various methods to estimate the scene flow. Most of the methods use motion estimation with stereo re-construction. This paper describes an interesting way to fuse the video from two camera's and create a 3D reconstruction. The proposed algorithm incorporates probabilistic distributions for optical flow and disparity. Multiple such re-created renderings can be put together to create re-timed movies of the event, with the resulting visual experience richer than that of a regular video clip, or switching between images from multiple cameras, do a head tracking of the viewer and change the view angle accordingly or view it on a mobile device using the accelerometer for camera tilting for the 3D effect.","PeriodicalId":348804,"journal":{"name":"International Conference on Advances in Computing and Artificial Intelligence","volume":"115 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scene flow estimation from stereo video source\",\"authors\":\"Aniket Bera\",\"doi\":\"10.1145/2007052.2007058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are various methods to estimate the scene flow. Most of the methods use motion estimation with stereo re-construction. This paper describes an interesting way to fuse the video from two camera's and create a 3D reconstruction. The proposed algorithm incorporates probabilistic distributions for optical flow and disparity. Multiple such re-created renderings can be put together to create re-timed movies of the event, with the resulting visual experience richer than that of a regular video clip, or switching between images from multiple cameras, do a head tracking of the viewer and change the view angle accordingly or view it on a mobile device using the accelerometer for camera tilting for the 3D effect.\",\"PeriodicalId\":348804,\"journal\":{\"name\":\"International Conference on Advances in Computing and Artificial Intelligence\",\"volume\":\"115 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Advances in Computing and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2007052.2007058\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Advances in Computing and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2007052.2007058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
There are various methods to estimate the scene flow. Most of the methods use motion estimation with stereo re-construction. This paper describes an interesting way to fuse the video from two camera's and create a 3D reconstruction. The proposed algorithm incorporates probabilistic distributions for optical flow and disparity. Multiple such re-created renderings can be put together to create re-timed movies of the event, with the resulting visual experience richer than that of a regular video clip, or switching between images from multiple cameras, do a head tracking of the viewer and change the view angle accordingly or view it on a mobile device using the accelerometer for camera tilting for the 3D effect.