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dc.contributor.authorKim, Youngmin
dc.contributor.authorMitra, Niloy J.
dc.contributor.authorYan, Dongming
dc.contributor.authorGuibas, Leonidas J.
dc.date.accessioned2015-08-24T09:26:15Z
dc.date.available2015-08-24T09:26:15Z
dc.date.issued2012-11-01
dc.identifier.issn07300301
dc.identifier.doi10.1145/2366145.2366157
dc.identifier.urihttp://hdl.handle.net/10754/575789
dc.description.abstractLarge-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.
dc.description.sponsorshipWe 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.
dc.publisherAssociation for Computing Machinery (ACM)
dc.subjectAcquisition
dc.subjectRealtime Modeling
dc.subjectScene understanding
dc.subjectShape analysis
dc.titleAcquiring 3D indoor environments with variability and repetition
dc.typeConference Paper
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentVisual Computing Center (VCC)
dc.identifier.journalACM Transactions on Graphics
dc.conference.date2 – 5 November 2015
dc.conference.nameProceedings of ACM SIGGRAPH Asia 2012
dc.conference.locationKobe, Japan
dc.contributor.institutionStanford University, United States
dc.contributor.institutionUniv. College London, United Kingdom
kaust.personMitra, Niloy J.
kaust.personYan, Dongming


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