State of the Art on 3D Reconstruction with RGB-D Cameras

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dc.contributor.authorZollhöfer, Michaelen_US
dc.contributor.authorStotko, Patricken_US
dc.contributor.authorGörlitz, Andreasen_US
dc.contributor.authorTheobalt, Christianen_US
dc.contributor.authorNießner, Matthiasen_US
dc.contributor.authorKlein, Reinharden_US
dc.contributor.authorKolb, Andreasen_US
dc.contributor.editorHildebrandt, Klaus and Theobalt, Christianen_US
dc.date.accessioned2018-04-14T18:35:29Z
dc.date.available2018-04-14T18:35:29Z
dc.date.issued2018
dc.description.abstractThe advent of affordable consumer grade RGB-D cameras has brought about a profound advancement of visual scene reconstruction methods. Both computer graphics and computer vision researchers spend significant effort to develop entirely new algorithms to capture comprehensive shape models of static and dynamic scenes with RGB-D cameras. This led to significant advances of the state of the art along several dimensions. Some methods achieve very high reconstruction detail, despite limited sensor resolution. Others even achieve real-time performance, yet possibly at lower quality. New concepts were developed to capture scenes at larger spatial and temporal extent. Other recent algorithms flank shape reconstruction with concurrent material and lighting estimation, even in general scenes and unconstrained conditions. In this state-of-the-art report, we analyze these recent developments in RGB-D scene reconstruction in detail and review essential related work. We explain, compare, and critically analyze the common underlying algorithmic concepts that enabled these recent advancements. Furthermore, we show how algorithms are designed to best exploit the benefits of RGB-D data while suppressing their often non-trivial data distortions. In addition, this report identifies and discusses important open research questions and suggests relevant directions for future work.en_US
dc.description.documenttypestar
dc.description.number2
dc.description.sectionheadersState of the Art Reports
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume37
dc.identifier.doi10.1111/cgf.13386
dc.identifier.issn1467-8659
dc.identifier.pages625-652
dc.identifier.urihttps://doi.org/10.1111/cgf.13386
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13386
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputing methodologies
dc.subjectReconstruction
dc.subjectAppearance and texture representations
dc.subjectMotion capture
dc.titleState of the Art on 3D Reconstruction with RGB-D Camerasen_US
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