| Scanning 3D Full Human Bodies Using Kinects. | |
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MedLine Citation:
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PMID: 22402692 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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Depth camera such as Microsoft Kinect, is much cheaper than conventional 3D scanning devices, and thus it can be acquired for everyday users easily. However, the depth data captured by Kinect over a certain distance is of extreme low quality. In this paper, we present a novel scanning system for capturing 3D full human body models by using multiple Kinects. To avoid the interference phenomena, we use two Kinects to capture the upper part and lower part of a human body respectively without overlapping region. A third Kinect is used to capture the middle part of the human body from the opposite direction. We propose a practical approach for registering the various body parts of different views under non-rigid deformation. First, a rough mesh template is constructed and used to deform successive frames pairwisely. Second, global alignment is performed to distribute errors in the deformation space, which can solve the loop closure problem efficiently. Misalignment caused by complex occlusion can also be handled reasonably by our global alignment algorithm. The experimental results have shown the efficiency and applicability of our system. Our system obtains impressive results in a few minutes with low price devices, thus is practically useful for generating personalized avatars for everyday users. Our system has been used for 3D human animation and virtual try on, and can further facilitate a range of home–oriented virtual reality (VR) applications. |
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Authors:
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Jing Tong; Jin Zhou; Ligang Liu; Zhigeng Pan; Hao Yan |
Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: IEEE transactions on visualization and computer graphics Volume: 18 ISSN: 1077-2626 ISO Abbreviation: IEEE Trans Vis Comput Graph Publication Date: 2012 Apr |
Date Detail:
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Created Date: 2012-03-09 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9891704 Medline TA: IEEE Trans Vis Comput Graph Country: United States |
Other Details:
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Languages: eng Pagination: 643-50 Citation Subset: IM |
Affiliation:
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Zhejiang University and HoHai University. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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