Matheus A. Bergmann, Paulo G. L. Pinto, T. L. T. D. Silveira, C. Jung
{"title":"Gravity Alignment for Single Panorama Depth Inference","authors":"Matheus A. Bergmann, Paulo G. L. Pinto, T. L. T. D. Silveira, C. Jung","doi":"10.1109/sibgrapi54419.2021.00015","DOIUrl":null,"url":null,"abstract":"Monocular depth inference methods based on 360° images allow 3D reconstruction of entire rooms with a single capture. However, most state-of-the-art approaches assume gravity-aligned images and are highly sensitive to camera rotations. Such limitations result in poor depth estimates, which may jeopardize further 3D-based applications. Here, we present a pipeline for spherical single-image depth inference supplied by a novel rotation correction module. We show that our gravity alignment module can improve existing single-image depth estimation methods, being also useful for aligning color and depth to the horizon, which is highly desirable in many applications.","PeriodicalId":197423,"journal":{"name":"2021 34th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 34th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/sibgrapi54419.2021.00015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Monocular depth inference methods based on 360° images allow 3D reconstruction of entire rooms with a single capture. However, most state-of-the-art approaches assume gravity-aligned images and are highly sensitive to camera rotations. Such limitations result in poor depth estimates, which may jeopardize further 3D-based applications. Here, we present a pipeline for spherical single-image depth inference supplied by a novel rotation correction module. We show that our gravity alignment module can improve existing single-image depth estimation methods, being also useful for aligning color and depth to the horizon, which is highly desirable in many applications.