A Framework for Object Recognition in Construction Using Building Information Modeling and High Frame Rate 3D Imaging

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dc.contributor.authorLytle, Alan Marshallen
dc.contributor.committeechairSinha, Sunil Kumaren
dc.contributor.committeememberBeliveau, Yvan J.en
dc.contributor.committeememberBulbul, Tanyelen
dc.contributor.committeememberGolparvar-Fard, Manien
dc.contributor.departmentCivil Engineeringen
dc.date.accessioned2014-03-14T20:09:42Zen
dc.date.adate2011-04-25en
dc.date.available2014-03-14T20:09:42Zen
dc.date.issued2011-04-01en
dc.date.rdate2011-04-25en
dc.date.sdate2011-04-15en
dc.description.abstractObject recognition systems require baseline information upon which to compare sensed data to enable a recognition task. The ability to integrate a diverse set of object recognition data for different components in a Building Information Model (BIM) will enable many autonomous systems to access and use these data in an on-demand learning capacity, and will accelerate the integration of object recognition systems in the construction environment. This research presents a new framework for linking feature descriptors to a BIM to support construction object recognition. The proposed framework is based upon the Property and External Reference Resource schemas within the IFC 2x3 TC1 architecture. Within this framework a new Property Set (Pset_ObjectRecognition) is suggested which provides an on-demand capability to access available feature descriptor information either embedded in the IFC model or referenced in an external model database. The Property Set is extensible, and can be modified and adjusted as required for future research and field implementation. With this framework multiple sets of feature descriptors associated with different sensing modalities and different algorithms can all be aggregated into one Property Set and assigned to either object types or object instances.en
dc.description.degreePh. D.en
dc.identifier.otheretd-04152011-111750en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-04152011-111750/en
dc.identifier.urihttp://hdl.handle.net/10919/26888en
dc.publisherVirginia Techen
dc.relation.haspartLytle_AM_D_2011.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectBuilding Information Modelingen
dc.subjectBIMen
dc.subjectIndustry Foundation Classesen
dc.subjectObject Recognitionen
dc.subject3D Imagingen
dc.subjectIFCen
dc.titleA Framework for Object Recognition in Construction Using Building Information Modeling and High Frame Rate 3D Imagingen
dc.typeDissertationen
thesis.degree.disciplineCivil Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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