Real-Time Sphere Sweeping Stereo From Multiview Fisheye Images

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dc.contributor.authorMeuleman, Andreasko
dc.contributor.authorJang, Hyeongjoongko
dc.contributor.authorJeon, Danielko
dc.contributor.authorKim, Min Hyukko
dc.date.accessioned2021-06-10T07:30:20Z-
dc.date.available2021-06-10T07:30:20Z-
dc.date.created2021-06-10-
dc.date.created2021-06-10-
dc.date.created2021-06-10-
dc.date.created2021-06-10-
dc.date.created2021-06-10-
dc.date.created2021-06-10-
dc.date.issued2021-06-24-
dc.identifier.citationIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)-
dc.identifier.issn1063-6919-
dc.identifier.urihttp://hdl.handle.net/10203/285736-
dc.description.abstractA set of cameras with fisheye lenses have been used to capture a wide field of view. The traditional scan-line stereo algorithms based on epipolar geometry are directly inapplicable to this non-pinhole camera setup due to optical characteristics of fisheye lenses; hence, existing complete 360◦ RGB-D imaging systems have rarely achieved realtime performance yet. In this paper, we introduce an efficient sphere-sweeping stereo that can run directly on multiview fisheye images without requiring additional spherical rectification. Our main contributions are: First, we introduce an adaptive spherical matching method that accounts for each input fisheye camera’s resolving power concerning spherical distortion. Second, we propose a fast inter-scale bilateral cost volume filtering method that refines distance in noisy and textureless regions with optimal complexity of O(n). It enables real-time dense distance estimation while preserving edges. Lastly, the fisheye color and distance images are seamlessly combined into a complete 360◦ RGB-D image via fast inpainting of the dense distance map. We demonstrate an embedded 360◦ RGB-D imaging prototype composed of a mobile GPU and four fisheye cameras. Our prototype is capable of capturing complete 360◦ RGB-D videos with a resolution of two megapixels at 29 fps. Results demonstrate that our real-time method outperforms traditional omnidirectional stereo and learning-based omnidirectional stereo in terms of accuracy and performance.-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleReal-Time Sphere Sweeping Stereo From Multiview Fisheye Images-
dc.typeConference-
dc.identifier.wosid000742075001060-
dc.type.rimsCONF-
dc.citation.publicationnameIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationVirtual-
dc.identifier.doi10.1109/CVPR46437.2021.01126-
dc.contributor.localauthorKim, Min Hyuk-
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CS-Conference Papers(학술회의논문)
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