3D Indoor Building Environment Reconstruction using Polynomial Kernel, Least Square Adjustment, Interval Analysis and Homotopy Continuation

Ali Jamali, Alias Abdul Rahman, Francesc/François Antón Castro, Darka Mioc

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Abstract

Nowadays, municipalities intend to have 3D city models for facility management, disaster management and architectural planning. Indoor models can be reconstructed from construction plans but sometimes, they are not available or very often, they differ from ‘as-built’ plans. In this case, the buildings and their rooms must be surveyed. One of the most utilized methods of indoor surveying is laser scanning. The laser scanning method allows taking accurate and detailed measurements. However, Terrestrial Laser Scanner is costly and time consuming. In this paper, several techniques for indoor 3D building data acquisition have been investigated. For reducing the time and cost of indoor building data acquisition process, the Trimble LaserAce 1000 range finder is used. The proposed approache use relatively cheap equipment: a light Laser Rangefinder which appear to be feasible, but it needs to be tested to see if the observation accuracy is sufficient for the 3D building modelling. The accuracy of the rangefinder is evaluated and a simple spatial model is reconstructed from real data. This technique is rapid (it requires a shorter time as compared to others), but the results show inconsistencies in horizontal angles for short distances in indoor environments. The range finder horizontal angle sensor was calibrated using a least square adjustment algorithm, a polynomial kernel, interval analysis and homotopy continuation.
Original languageEnglish
Title of host publicationProceedings of GeoAdvances 2016
Publication date2016
Pages103-113
DOIs
Publication statusPublished - 2016
EventGeoAdvances 2016: ISPRS Workshop on Multi-dimensional & Multi-scale Spatial Data Modeling - Mimar Sinan Fine Arts University, Istanbul, Turkey
Duration: 16 Oct 201617 Oct 2016
http://geoadvances.org/

Conference

ConferenceGeoAdvances 2016: ISPRS Workshop on Multi-dimensional & Multi-scale Spatial Data Modeling
LocationMimar Sinan Fine Arts University
CountryTurkey
CityIstanbul
Period16/10/201617/10/2016
Internet address
SeriesInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
ISSN1682-1750

Keywords

  • Indoor surveying
  • Least square adjustment
  • Interval analysis
  • Laser scanning
  • Calibration
  • Homotopy continuation
  • Polynomial kernel

Cite this

Jamali, A., Rahman, A. A., Antón Castro, FF., & Mioc, D. (2016). 3D Indoor Building Environment Reconstruction using Polynomial Kernel, Least Square Adjustment, Interval Analysis and Homotopy Continuation. In Proceedings of GeoAdvances 2016 (pp. 103-113). International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences https://doi.org/10.5194/isprs-archives-XLII-2-W1-103-2016
Jamali, Ali ; Rahman, Alias Abdul ; Antón Castro, Francesc/François ; Mioc, Darka. / 3D Indoor Building Environment Reconstruction using Polynomial Kernel, Least Square Adjustment, Interval Analysis and Homotopy Continuation. Proceedings of GeoAdvances 2016 . 2016. pp. 103-113 (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences).
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title = "3D Indoor Building Environment Reconstruction using Polynomial Kernel, Least Square Adjustment, Interval Analysis and Homotopy Continuation",
abstract = "Nowadays, municipalities intend to have 3D city models for facility management, disaster management and architectural planning. Indoor models can be reconstructed from construction plans but sometimes, they are not available or very often, they differ from ‘as-built’ plans. In this case, the buildings and their rooms must be surveyed. One of the most utilized methods of indoor surveying is laser scanning. The laser scanning method allows taking accurate and detailed measurements. However, Terrestrial Laser Scanner is costly and time consuming. In this paper, several techniques for indoor 3D building data acquisition have been investigated. For reducing the time and cost of indoor building data acquisition process, the Trimble LaserAce 1000 range finder is used. The proposed approache use relatively cheap equipment: a light Laser Rangefinder which appear to be feasible, but it needs to be tested to see if the observation accuracy is sufficient for the 3D building modelling. The accuracy of the rangefinder is evaluated and a simple spatial model is reconstructed from real data. This technique is rapid (it requires a shorter time as compared to others), but the results show inconsistencies in horizontal angles for short distances in indoor environments. The range finder horizontal angle sensor was calibrated using a least square adjustment algorithm, a polynomial kernel, interval analysis and homotopy continuation.",
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author = "Ali Jamali and Rahman, {Alias Abdul} and {Ant{\'o}n Castro}, Francesc/Fran{\cc}ois and Darka Mioc",
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Jamali, A, Rahman, AA, Antón Castro, FF & Mioc, D 2016, 3D Indoor Building Environment Reconstruction using Polynomial Kernel, Least Square Adjustment, Interval Analysis and Homotopy Continuation. in Proceedings of GeoAdvances 2016 . International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, pp. 103-113, GeoAdvances 2016: ISPRS Workshop on Multi-dimensional & Multi-scale Spatial Data Modeling, Istanbul, Turkey, 16/10/2016. https://doi.org/10.5194/isprs-archives-XLII-2-W1-103-2016

3D Indoor Building Environment Reconstruction using Polynomial Kernel, Least Square Adjustment, Interval Analysis and Homotopy Continuation. / Jamali, Ali; Rahman, Alias Abdul; Antón Castro, Francesc/François; Mioc, Darka.

Proceedings of GeoAdvances 2016 . 2016. p. 103-113 (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences).

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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AB - Nowadays, municipalities intend to have 3D city models for facility management, disaster management and architectural planning. Indoor models can be reconstructed from construction plans but sometimes, they are not available or very often, they differ from ‘as-built’ plans. In this case, the buildings and their rooms must be surveyed. One of the most utilized methods of indoor surveying is laser scanning. The laser scanning method allows taking accurate and detailed measurements. However, Terrestrial Laser Scanner is costly and time consuming. In this paper, several techniques for indoor 3D building data acquisition have been investigated. For reducing the time and cost of indoor building data acquisition process, the Trimble LaserAce 1000 range finder is used. The proposed approache use relatively cheap equipment: a light Laser Rangefinder which appear to be feasible, but it needs to be tested to see if the observation accuracy is sufficient for the 3D building modelling. The accuracy of the rangefinder is evaluated and a simple spatial model is reconstructed from real data. This technique is rapid (it requires a shorter time as compared to others), but the results show inconsistencies in horizontal angles for short distances in indoor environments. The range finder horizontal angle sensor was calibrated using a least square adjustment algorithm, a polynomial kernel, interval analysis and homotopy continuation.

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EP - 113

BT - Proceedings of GeoAdvances 2016

ER -

Jamali A, Rahman AA, Antón Castro FF, Mioc D. 3D Indoor Building Environment Reconstruction using Polynomial Kernel, Least Square Adjustment, Interval Analysis and Homotopy Continuation. In Proceedings of GeoAdvances 2016 . 2016. p. 103-113. (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences). https://doi.org/10.5194/isprs-archives-XLII-2-W1-103-2016