Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W1, 103-113, 2016
https://doi.org/10.5194/isprs-archives-XLII-2-W1-103-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
26 Oct 2016
3D Indoor Building Environment Reconstruction using Least Square Adjustment, Polynomial Kernel, Interval Analysis and Homotopy Continuation
Ali Jamali1, François Anton2, Alias Abdul Rahman1, and Darka Mioc2 1Universiti Teknologi Malaysia (UTM) Faculty of Geoinformation and Real Estate, Malaysia
2Technical University of Denmark, Denmark National Space Institute, Denmark
Keywords: Indoor surveying, least square adjustment, interval analysis, laser scanning, calibration, 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.
Conference paper (PDF, 1103 KB)


Citation: Jamali, A., Anton, F., Rahman, A. A., and Mioc, D.: 3D Indoor Building Environment Reconstruction using Least Square Adjustment, Polynomial Kernel, Interval Analysis and Homotopy Continuation, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W1, 103-113, https://doi.org/10.5194/isprs-archives-XLII-2-W1-103-2016, 2016.

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