DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kweon, In-So | - |
dc.contributor.advisor | 권인소 | - |
dc.contributor.author | Han, Yu-Deog | - |
dc.contributor.author | 한유덕 | - |
dc.date.accessioned | 2015-04-23T07:09:14Z | - |
dc.date.available | 2015-04-23T07:09:14Z | - |
dc.date.issued | 2013 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=567275&flag=dissertation | - |
dc.identifier.uri | http://hdl.handle.net/10203/197248 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 미래자동차학제전공, 2013.2, [ v, 46 p. ] | - |
dc.description.abstract | We present an optimization-based framework to estimate both natural lighting conditions and high quality shape information using a single RGB-D image of diffuse objects. To estimate accurate natural lighting conditions, we present a general lighting model consisting of global and local models. The global lighting model is robustly estimated from the RGB-D input with a low-dimensional characteristic of the diffuse lighting model. The local lighting model can represent spatially varying illumination due to attached shadows, inter-reflections, and near lightings. With both the global and local lighting model, we can model complex lighting variations that previous methods cannot account for. For high quality shape capture, a shape from shading approach is applied with the estimated lighting model. Use of a geometric normal constraint greatly reduces local ambiguity in determining local surface orientation. Since both lighting conditions and shape estimations are done with a single RGB-D image, our method can capture the high quality shape of dynamic objects under uncalibrated varying illumination conditions. Experimental results using RGB-D images of a variety of diffuse objects in natural lighting conditions demonstrate the feasibility and effectiveness of the method to dramatically improve the limited low depth resolution of depth cameras, such as Kinect. | eng |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | 3D modeling | - |
dc.subject | 깊이 센서 | - |
dc.subject | 키넥트 | - |
dc.subject | Shape from shading | - |
dc.subject | 3차원 모델링 | - |
dc.subject | Kinect | - |
dc.subject | Shape from shading | - |
dc.subject | Natural illumination | - |
dc.title | High quality shape capture from an RGB-D image under uncalibrated natural illumination | - |
dc.title.alternative | 단일 RGB-D 영상을 이용한 임의의 조명에서의 고품질 3차원 모델링 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 567275/325007 | - |
dc.description.department | 한국과학기술원 : 미래자동차학제전공, | - |
dc.identifier.uid | 020114205 | - |
dc.contributor.localauthor | Kweon, In-So | - |
dc.contributor.localauthor | 권인소 | - |
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