Lytle, A M (2011) A framework for object recognition in construction using building information modeling and high frame rate three-dimensional imaging. PhD thesis, Virginia Polytechnic Institute and State University, USA.
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.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Sinha, S |
| Uncontrolled Keywords: | building information model; building information modeling; integration; learning |
| Index terms: | implementation, building information modelling, object recognition, database, integration |
| Subjects: | data management, organizational analysis, information systems, computer vision, contractual arrangements |
| Topics: | Procurement, Digital Applications, Organizational Design |
| Descriptive scope: | 2 PC |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here