Memory‐Efficient Interactive Online Reconstruction From Depth Image Streams

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dc.contributor.authorReichl, F.en_US
dc.contributor.authorWeiss, J.en_US
dc.contributor.authorWestermann, R.en_US
dc.contributor.editorChen, Min and Zhang, Hao (Richard)en_US
dc.date.accessioned2016-12-08T11:25:36Z
dc.date.available2016-12-08T11:25:36Z
dc.date.issued2016
dc.description.abstractWe describe how the pipeline for 3D online reconstruction using commodity depth and image scanning hardware can be made scalable for large spatial extents and high scanning resolutions. Our modified pipeline requires less than 10% of the memory that is required by previous approaches at similar speed and resolution. To achieve this, we avoid storing a 3D distance field and weight map during online scene reconstruction. Instead, surface samples are binned into a high‐resolution binary voxel grid. This grid is used in combination with caching and deferred processing of depth images to reconstruct the scene geometry. For pose estimation, GPU ray‐casting is performed on the binary voxel grid. A one‐to‐one comparison to level‐set ray‐casting in a distance volume indicates slightly lower pose accuracy. To enable unlimited spatial extents and store acquired samples at the appropriate level of detail, we combine a hash map with a hierarchical tree representation.en_US
dc.description.number8
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume35
dc.identifier.doi10.1111/cgf.12779
dc.identifier.issn1467-8659
dc.identifier.urihttp://dx.doi.org/10.1111/cgf.12779
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf12779
dc.publisher© 2016 The Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectobject scanning/acquisition
dc.subjectsurface reconstruction
dc.subjectI.3.3 [Computer Graphics]: Picture/Image Generation—Digitizing and Scanning
dc.titleMemory‐Efficient Interactive Online Reconstruction From Depth Image Streamsen_US
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