DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ha, Hyunho | ko |
dc.contributor.author | Lee, Joo Ho | ko |
dc.contributor.author | Meuleman, Andreas | ko |
dc.contributor.author | Kim, Min Hyuk | ko |
dc.date.accessioned | 2021-06-10T07:50:21Z | - |
dc.date.available | 2021-06-10T07:50:21Z | - |
dc.date.created | 2021-06-10 | - |
dc.date.created | 2021-06-10 | - |
dc.date.created | 2021-06-10 | - |
dc.date.created | 2021-06-10 | - |
dc.date.created | 2021-06-10 | - |
dc.date.issued | 2021-06-25 | - |
dc.identifier.citation | IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp.15965 - 15974 | - |
dc.identifier.issn | 1063-6919 | - |
dc.identifier.uri | http://hdl.handle.net/10203/285739 | - |
dc.description.abstract | Multiview shape-from-shading (SfS) has achieved high-detail geometry, but its computation is expensive for solving a multiview registration and an ill-posed inverse rendering problem. Therefore, it has been mainly used for offline methods. Volumetric fusion enables real-time scanning using a conventional RGB-D camera, but its geometry resolution has been limited by the grid resolution of the volumetric distance field and depth registration errors. In this paper, we propose a real-time scanning method that can acquire high-detail geometry by bridging volumetric fusion and multiview SfS in two steps. First, we propose the first real-time acquisition of photometric normals stored in texture space to achieve high-detail geometry. We also introduce geometry-aware texture mapping, which progressively refines geometric registration between the texture space and the volumetric distance field by means of normal texture, achieving real-time multiview SfS. We demonstrate our scanning of high-detail geometry using an RGB-D camera at ~20 fps. Results verify that the geometry quality of our method is strongly competitive with that of offline multi-view SfS methods. | - |
dc.language | English | - |
dc.publisher | IEEE | - |
dc.title | NormalFusion: Real-Time Acquisition of Surface Normals for High-Resolution RGB-D Scanning | - |
dc.type | Conference | - |
dc.identifier.wosid | 000742075006019 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 15965 | - |
dc.citation.endingpage | 15974 | - |
dc.citation.publicationname | IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Virtual | - |
dc.identifier.doi | 10.1109/CVPR46437.2021.01571 | - |
dc.contributor.localauthor | Kim, Min Hyuk | - |
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