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    Acquiring 3D indoor environments with variability and repetition

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    Type
    Conference Paper
    Authors
    Kim, Youngmin
    Mitra, Niloy J. cc
    Yan, Dongming cc
    Guibas, Leonidas J.
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Visual Computing Center (VCC)
    Date
    2012-11-01
    Permanent link to this record
    http://hdl.handle.net/10754/575789
    
    Metadata
    Show full item record
    Abstract
    Large-scale acquisition of exterior urban environments is by now a well-established technology, supporting many applications in search, navigation, and commerce. The same is, however, not the case for indoor environments, where access is often restricted and the spaces are cluttered. Further, such environments typically contain a high density of repeated objects (e.g., tables, chairs, monitors, etc.) in regular or non-regular arrangements with significant pose variations and articulations. In this paper, we exploit the special structure of indoor environments to accelerate their 3D acquisition and recognition with a low-end handheld scanner. Our approach runs in two phases: (i) a learning phase wherein we acquire 3D models of frequently occurring objects and capture their variability modes from only a few scans, and (ii) a recognition phase wherein from a single scan of a new area, we identify previously seen objects but in different poses and locations at an average recognition time of 200ms/model. We evaluate the robustness and limits of the proposed recognition system using a range of synthetic and real world scans under challenging settings. © 2012 ACM.
    Sponsors
    We acknowledge the support of a gift from Qualcomm Corporation, the Max Planck Center for Visual Computing and Communications, NSF grants 0914833 and 1011228, a KAUST AEA grant, and Marie Curie Career Integration Grant 303541.
    Publisher
    Association for Computing Machinery (ACM)
    Journal
    ACM Transactions on Graphics
    Conference/Event name
    Proceedings of ACM SIGGRAPH Asia 2012
    DOI
    10.1145/2366145.2366157
    ae974a485f413a2113503eed53cd6c53
    10.1145/2366145.2366157
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Visual Computing Center (VCC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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