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Virginia Tech

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

Abstract

dc:description.abstract

Object 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.

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Civil Engineering
Department dc:contributor.department
Civil Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2011

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Lytle, Alan Marshall
Chair dc:contributor.committeechair
  • Sinha, Sunil Kumar
Committee members dc:contributor.committeemember
  • Beliveau, Yvan J.
  • Bulbul, Tanyel
  • Golparvar-Fard, Mani

Subjects

dc:subject × 6

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-04152011-111750
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/26888

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Lytle, Alan Marshall. A Framework for Object Recognition in Construction Using Building Information Modeling and High Frame Rate 3D Imaging. doctoral thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/26888