Abstract
Among several others, the on-site inspection process is mainly concerned with finding the right design and specifications information needed to inspect each newly constructed segment or element. While inspecting steel erection, for example, inspectors need to locate the right drawings for each member and the corresponding specifications sections that describe the allowable deviations in placement among others. These information seeking tasks are highly monotonous, time consuming and often erroneous, due to the high similarity of drawings and constructed elements and the abundance of information involved which can confuse the inspector. To address this problem, this paper presents the first steps of research that is investigating the requirements of an automated computer vision-based approach to automatically identify “as-built” information and use it to retrieve “as-designed” project information for field construction, inspection, and maintenance tasks. Under this approach, a visual pattern recognition model was developed that aims to allow automatic identification of construction entities and materials visible in the camera’s field of view at a given time and location, and automatic retrieval of relevant design and specifications information.
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References
Abudayyeh, O.Y.: Audio/Visual Information in Construction Project Control. Journal of Advances in Engineering Software 28(2) (March 1997)
Garcia, A.C.B., Kunz, J., Ekstrom, M., Kiviniemi, A.: Building a project ontology with extreme collaboration and virtual design and construction. Advanced Engineering Informatics 18(2), 71–85 (2004)
Brilakis, I., Soibelman, L.: Multi-Modal Image Retrieval from Construction Databases and Model-Based Systems. Journal of Construction Engineering and Management, American Society of Civil Engineers (in print, 2006)
Brilakis, I., Soibelman, L., Shinagawa, Y.: Material-Based Construction Site Image Retrieval. Journal of Computing in Civil Engineering, American Society of Civil Engineers 19(4) (October 2005)
Brilakis, I., Soibelman, L., Shinagawa, Y.: Construction Site Image Retrieval Based on Material Cluster Recognition. Journal of Advanced Engineering Informatics (in print, 2006)
Brilakis, I., Soibelman, L.: Shape-Based Retrieval of Construction Site Photographs. Journal of Computing in Civil Engineering (in review, 2006)
Brilakis, I., Soibelman, L.: Content-Based Search Engines for Construction Image Databases. Journal of Automation in Construction 14(4), 537–550 (2005)
Rui, Y., Huang, T.S., Ortega, M., Mehrotra, S.: Relevance Feedback: A Power Tool in Interactive Content-Based Image Retrieval. IEEE Tran. on Circuits and Systems for Video Technology 8(5), 644–655 (1998)
Natsev, A., Rastogi, R., Shim, K.: Walrus: A Similarity Retrieval Algorithm for Image Databases. In: Proc. ACM-SIGMOD Conf. On Management of Data (SIGMOD 1999), Philadelphia, PA, pp. 395–406 (1999)
Zhou, X.S., Huang, T.S.: Comparing Discriminating Transformations and SVM for learning during Multimedia Retrieval. In: ACM Multimedia, Ottawa, Canada (2001)
Bovik, A.: Handbook of Image and Video Processing, 1st edn. Academic Press, London (2000)
Forsyth, D., Ponce, J.: Computer Vision - A modern approach, 1st edn. Prentice Hall, Englewood Cliffs (2002)
Shin, S., Hryciw, R.D.: Wavelet Analysis of Soil Mass Images for Particle Size Determination. Journal of Computing in Civil Engineering 18(1), 19–27 (2004)
Lipman, R.: Mobile 3D Visualization for Construction. In: Proceedings of the 19th International Symposium on Automation and Robotics in Construction, Gaithersburg, MD, September 23-25 (2002)
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Brilakis, I.K. (2006). Automated On-site Retrieval of Project Information. In: Smith, I.F.C. (eds) Intelligent Computing in Engineering and Architecture. EG-ICE 2006. Lecture Notes in Computer Science(), vol 4200. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11888598_10
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DOI: https://doi.org/10.1007/11888598_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46246-0
Online ISBN: 978-3-540-46247-7
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