[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
research-article

A videogrammetric as-built data collection method for digital fabrication of sheet metal roof panels

Published: 01 October 2013 Publication History

Abstract

A roofing contractor typically needs to acquire as-built dimensions of a roof structure several times over the course of its build because a structure is never built to the exact drawing dimensions. In the construction phase and in order to digitally fabricate sheet metal roof panels, the contractor has to measure end-to-end dimensions of boundaries of every roof plane with a certain level of accuracy (i.e., errors less than 2cm). This is necessary to be able to cut sheet metal coil such that different pieces perfectly fit together. Obtaining these measurements using the exiting roof surveying methods could be costly in terms of equipment, labor, and/or worker exposure to safety hazards. This paper presents a video-based surveying framework as an alternative method which is simple to use, automated, less expensive, and safe. When using this framework, the contractor collects video streams with a calibrated stereo camera set. The captured data is processed to automatically generate a 3D wire-diagram of the target roof. Measurements from the wire-diagram are saved in a digital file (XML format) which could be loaded into an on-site sheet metal folding and cutting machine. Experimental analyses demonstrate applicability of the proposed framework.

References

[1]
NRCA Roofing Manual, National Roofing Contractors Association, 2012.
[2]
Izquierdo, S., Rodrigues, M. and Fueyo, N., A method for estimating the geographical distribution of the available roof surface area for large-scale photovoltaic energy-potential evaluations. Solar Energy. v82. 929-939.
[3]
H. Hashiba, K. Kameda, S. Tanaka, T. Sugimura, Digital roof model(DRM) using high resolution satellite image and its application for 3D mapping of city region, in: Proceedings of IEEE International Geoscience and Remote Sensing, Symposium, 2003.
[4]
Wood, D., Evaluating and estimating roofing damage. Estimating Today (American Society of Professional Estimators). 11-17.
[5]
Fredericks, T., Abudayyeh, O., Choi, S., Wiersma, M. and Charles, M., Occupational injuries and fatalities in the roofing contracting industry. Journal of Construction Engineering and Management. v131 i11. 1233-1240.
[6]
OSHA, Fall Protection. <http://www.osha.gov/SLTC/fallprotection/index.html> (accessed 10.12).
[7]
OSHA, Commonly Used Statistics. <http://www.osha.gov/oshstats/commonstats.html> (accessed 10.12).
[8]
L.H. Coaker, Reflector-Less Total Station Measurements and Their Accuracy, Precision and Reliability, Dissertation, University of Southern Queensland, 2009.
[9]
Leica 3D Disto - Tutorial Area and Volume: Roof Measurement, Leica Geosystems, 2012.
[10]
Case Study: Aerial Measurements Shown to Increase C-SAT, EagleView Technologies, 2012.
[11]
Tang, P., Akinci, B. and Huber, D., Quantification of edge loss of laser scanned data at spatial discontinuities. Automation in Construction. v18 i8. 1070-1083.
[12]
Dai, F., Rashidi, A., Brilakis, I. and Vela, P., Comparison of image- and time-of-flight-based technologies for 3D reconstruction of infrastructure. Journal of Construction Engineering and Management. v139 i1. 69-79.
[13]
Meng, L. and Forberg, A., 3D building generalisation. In: Challenges in the Portrayal of Geographic Information, The Netherlands, Elsevier Science, Amsterdam.
[14]
Pollefeys, M., Nister, D., Frahm, J., Akbarzadeh, A., Mordohai, P., Clipp, B., Engels, C., Gallup, D., Kim, S., Merrell, P., Salmi, C., Sinha, S., Talton, B., Wang, L., Yang, Q., Stewenius, R., Welch, G. and Towles, H., Detailed real-time urban 3D reconstruction from video. International Journal of Computer Vision. v78 i2-3. 143-167.
[15]
D. Gallup, Efficient 3D Reconstruction of Large-Scale Urban Environments from Street-Level Video, Dissertation, University of North Carolina, 2011.
[16]
Irschara, A., Zach, C., Klopschitz, M. and Bischof, H., Large-scale, dense city reconstruction from user-contributed photos. Computer Vision and Image Understanding. v116 i1. 2-15.
[17]
Podbreznik, P. and Potocnik, B., Estimating correspondence between arbitrarily selected points in two widely-separated views. Advanced Engineering Informatics. v24 i3. 367-376.
[18]
Fathi, H. and Brilakis, I., Automated sparse 3D point cloud generation of infrastructure using its distinctive visual features. Advanced Engineering Informatics. v25 i4. 760-770.
[19]
Brilakis, I., Fathi, H. and Rashidi, A., Progressive 3D reconstruction of infrastructure with videogrammetry. Automation in Construction. v20 i7. 884-895.
[20]
Jog, G., Fathi, H. and Brilakis, I., Automated computation of the fundamental matrix for vision based construction site applications. Advanced Engineering Informatics. v25 i4. 725-735.
[21]
M. Golparvar-Fard, F. Peña-Mora, S. Savarese, Automated progress monitoring using unordered daily construction photographs and IFC-based building information models, Journal of Computing in Civil Engineering, in press. http://dx.doi.org/10.1061/(ASCE)CP.1943-5487.0000205.
[22]
A. Rashidi, F. Dai, I. Brilakis, P. Vela, Optimized selection of key frames for monocular videogrammetric surveying of civil infrastructure, Advanced Engineering Informatics, 27 (2) (2013) 270-282.
[23]
Lowe, D., Distinctive image features from scale-invariant key points. International Journal of Computer Vision. v2 i60. 91-110.
[24]
Bay, H., Ess, A., Tuytelaars, T. and Gool, V.L., Speeded-up robust features (SURF). Computer Vision and Image Understanding. v110 i3. 346-359.
[25]
M. Goesele, N. Snavely, B. Curless, H. Hugues, S. M. Seitz, Mutli-view stereo for community photo collections, in: Proceedings of the International Conference on Computer Vision, Seattle, 2007.
[26]
Furukawa, Y. and Ponce, J., Accurate, dense, and robust multi-view stereopsis. IEEE Transactions on Pattern Analysis and Machine Intelligence. v32 i8. 1362-1376.
[27]
Fernandes, L. and Oliveira, M., Real-time line detection through an improved Hough transform voting scheme. Pattern Recognition. v41 i1. 299-314.
[28]
Von Gioi, R., Jakubowicz, J., Morel, J. and Randall, G., LSD: a fast line segment detector with a false detection control. IEEE Transaction on Pattern Analysis and Machine Intelligence. v32 i4. 722-732.
[29]
Akinlar, C. and Topal, C., EDLines: a real-time line segment detector with a false detection control. Pattern Recognition Letters. v32 i13. 1633-1642.
[30]
J. Rau, A line-based 3D roof model reconstruction algorithm: TIN-merging and reshaping (TMR), in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Melbourne, Australia, 2012.
[31]
T. Moons, D. Fr'ere, J. Vanderkerckhove, L. Van Gool, Automatic modeling and 3D reconstruction of urban house roofs from high resolution aerial imagery, in: Proceedings of the 5th European Conference on Computer Vision, Freiburg, Germany, 1998.
[32]
Baillard, C. and Zisserman, A., A plane-sweep strategy for the 3D reconstruction of buildings from multiple images. In: Proceedings of ISPRS Congress and Exhibition, Amsterdam.
[33]
S. Scholze, T. Moons, L. Van Gool, A probabilistic approach to building roof reconstruction using semantic labeling, in: Proceedings of DAGM, Zurich, 2002.
[34]
Suveg, I. and Vosselman, G., Reconstruction of 3D building models from aerial images and maps. ISPRS Journal of Photogrammetry and Remote Sensing. v58. 202-224.
[35]
Taylor, C.J. and Kriegman, D.J., Structure and motion from line segments in multiple images. IEEE Transaction on Pattern Analysis and Machine Intelligence. v17 i11. 1021-1032.
[36]
Cui, Y., Zhao, X. and Jing, C., An approach of aerial photogrammetry measurement based on 3D model. Key Engineering Materials. v500.
[37]
J. Jaw, C. Cheng, Building roof reconstruction by fusing laser range data and aerial images, in: Proceedings of the ISPRS Congress, 2008.
[38]
Sampath, A. and Shan, J., Segmentation and reconstruction of polyhedral building roofs from aerial lidar point clouds. IEEE Transactions on Geoscience and Remote Sensing. v48 i3. 1554-1567.
[39]
Cheng, L., Gong, J., Li, M. and Liu, Y., 3D building model reconstruction from multi-view aerial imagery and Lidar data. Photogrammetric Engineering and Remote Sensing. v77 i2. 125-139.
[40]
Christy, A. and Horaud, R., Iterative pose computation from line correspondences. Computer Vision and Image Understanding. v73 i1. 137-144.
[41]
S. Ramalingam, S. Bouaziz, P. Sturm, Pose estimation using both points and lines for geo-localization, in: Proceedings of IEEE International Conference on Robotics and Automation, 2011.
[42]
Pradeep, V. and Lim, J., Egomotion estimation using assorted features. International Journal of Computer Vision. v98 i2. 1-15.
[43]
H. Fathi, I. Brilakis, A videogrammetric as-built data collection framework for digital fabrication of sheet metal roof panels, in: Proceedings of the European Group for Intelligent Computing in Engineering, Munich, 2012.
[44]
Bartoli, A. and Sturm, P., Structure-from-motion using lines: representation, triangulation, and bundle adjustment. Computer Vision and Image Understanding. v100. 416-441.
[45]
Hartley, R., Lines and points in three views and the trifocal tensor. International Journal of Computer Vision. v22 i2. 125-140.
[46]
S. Sinha, D. Steedly, R. Szeliski, Piecewise planar stereo for image-based rendering, in: Proceedings of the International Conference on Computer Vision, Kyoto, 2009.
[47]
H. Fathi, I. Brilakis, Piecewise planar stereo for 3D reconstruction of built environments using point and line features, in: Proceedings of the European Group for Intelligent Computing in Engineering, Wien, 2013.
[48]
Hartley, R. and Zisserman, A., Multiple View Geometry in Computer Vision. 2003. Cambridge University Press, Cambridge.
[49]
J. Smith, S. Chang, Single color extraction and image query, in: Proceedings of the IEEE International Conference on Image Processing, 1995.
[50]
S. Scholze, T. Moons, L. Van Gool, A probabilistic approach to roof patch extraction and reconstruction, in: Proceedings of the Automatic Extraction of Man-Made Objects from Aerial and Space Images, 2001.
[51]
Wang, Z., Wu, F. and Hu, Z., MSLD: a robust descriptor for line matching. Pattern Recognition. v42 i5. 941-953.
[52]
Snavely, N., Seitz, S. and Szeliski, R., Modeling the world from internet photo collections. International Journal of Computer Vision. v80 i2. 189-210.
[53]
Werner, T., Zisserman, A. and Szeliski, R., New techniques for automated architectural reconstruction from photographs. In: Proceedings of ECCV, Springer, Berlin Heidelberg. pp. 541-555.

Cited By

View all
  • (2024)Image-based 3D reconstruction for Multi-Scale civil and infrastructure ProjectsAdvanced Engineering Informatics10.1016/j.aei.2023.10226859:COnline publication date: 1-Jan-2024
  • (2021)Multi-scale personnel deep feature detection algorithm based on Extended-YOLOv3Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-20077840:1(773-786)Online publication date: 1-Jan-2021
  • (2020)BIM-based task-level planning for robotic brick assembly through image-based 3D modelingAdvanced Engineering Informatics10.1016/j.aei.2019.10099343:COnline publication date: 1-Jan-2020
  • Show More Cited By
  1. A videogrammetric as-built data collection method for digital fabrication of sheet metal roof panels

        Recommendations

        Comments

        Please enable JavaScript to view thecomments powered by Disqus.

        Information & Contributors

        Information

        Published In

        cover image Advanced Engineering Informatics
        Advanced Engineering Informatics  Volume 27, Issue 4
        October, 2013
        255 pages

        Publisher

        Elsevier Science Publishers B. V.

        Netherlands

        Publication History

        Published: 01 October 2013

        Author Tags

        1. 3D roof modeling
        2. Digital fabrication
        3. Roof surveying
        4. Sheet metal roofing
        5. Structure from Motion
        6. Videogrammetry

        Qualifiers

        • Research-article

        Contributors

        Other Metrics

        Bibliometrics & Citations

        Bibliometrics

        Article Metrics

        • Downloads (Last 12 months)0
        • Downloads (Last 6 weeks)0
        Reflects downloads up to 14 Jan 2025

        Other Metrics

        Citations

        Cited By

        View all
        • (2024)Image-based 3D reconstruction for Multi-Scale civil and infrastructure ProjectsAdvanced Engineering Informatics10.1016/j.aei.2023.10226859:COnline publication date: 1-Jan-2024
        • (2021)Multi-scale personnel deep feature detection algorithm based on Extended-YOLOv3Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-20077840:1(773-786)Online publication date: 1-Jan-2021
        • (2020)BIM-based task-level planning for robotic brick assembly through image-based 3D modelingAdvanced Engineering Informatics10.1016/j.aei.2019.10099343:COnline publication date: 1-Jan-2020
        • (2018)Automated continuous construction progress monitoring using multiple workplace real time 3D scansAdvanced Engineering Informatics10.1016/j.aei.2018.06.00138:C(27-40)Online publication date: 1-Oct-2018
        • (2017)Fusion of Photogrammetry and Video Analysis for Productivity Assessment of Earthwork ProcessesComputer-Aided Civil and Infrastructure Engineering10.5555/3205242.320524532:2(107-123)Online publication date: 1-Feb-2017
        • (2015)Automated as-built 3D reconstruction of civil infrastructure using computer visionAdvanced Engineering Informatics10.1016/j.aei.2015.01.01229:2(149-161)Online publication date: 1-Apr-2015
        • (2013)Advanced computing for the built environmentAdvanced Engineering Informatics10.1016/j.aei.2013.11.00127:4(411-412)Online publication date: 1-Oct-2013

        View Options

        View options

        Media

        Figures

        Other

        Tables

        Share

        Share

        Share this Publication link

        Share on social media