Miko Atokari, Marko Viitanen, Alexandre Mercat, Emil Kattainen, Jarno Vanne
{"title":"Parallax-Tolerant 360 Live Video Stitcher","authors":"Miko Atokari, Marko Viitanen, Alexandre Mercat, Emil Kattainen, Jarno Vanne","doi":"10.1109/VCIP47243.2019.8965900","DOIUrl":null,"url":null,"abstract":"This paper presents an open-source software implementation for real-time 360-degree video stitching. To ensure a seamless stitching result, cylindrical and content-preserving warping are implemented to dynamically correct image alignment and parallax, which may drift due to scene changes, moving objects, or camera movement. Depth variation, color changes, and lighting differences between adjacent frames are also smoothed out to improve visual quality of the panoramic video. The system is benchmarked with six 1080p videos, which are stitched into 4096×732 pixel output format. The proposed algorithm attains an output rate of 18 frames per second on GeForce GTX 1070 GPU and real-time speed can be met with a high-end GPU.","PeriodicalId":388109,"journal":{"name":"2019 IEEE Visual Communications and Image Processing (VCIP)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Visual Communications and Image Processing (VCIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VCIP47243.2019.8965900","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents an open-source software implementation for real-time 360-degree video stitching. To ensure a seamless stitching result, cylindrical and content-preserving warping are implemented to dynamically correct image alignment and parallax, which may drift due to scene changes, moving objects, or camera movement. Depth variation, color changes, and lighting differences between adjacent frames are also smoothed out to improve visual quality of the panoramic video. The system is benchmarked with six 1080p videos, which are stitched into 4096×732 pixel output format. The proposed algorithm attains an output rate of 18 frames per second on GeForce GTX 1070 GPU and real-time speed can be met with a high-end GPU.