Mobile thermal mapping for matching of infrared images with 3D building models and 3D point clouds

References

• Kylili A, Fokaides PA, Christou P, et al. Infrared thermography (irt) applications for building diagnostics: a review. Appl Eng. 2014;134(Suppl C):531–549; Availablefrom: http://www.sciencedirect.com/science/article/pii/S0306261914008083.
   Google Scholar
• Klingert M. The usage of image processing methods for interpretation of thermography data. In: 17th International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering; 2006 Jul 12--14; Weimar, Germany; 2006.
   Google Scholar
• Fox M, Goodhew S, Wilde PD. Building defect detection: external versus internal thermography. Build Environ. 2016;105(Suppl C):317–331; Available from: http://www.sciencedirect.com/science/article/pii/S0360132316302189
   Google Scholar
• Haralick R, Joo H, Lee C, et al. Pose estimation from correspondence point data. SMC. 1989;19(6):1426–1446.
   Web of Science ®Google Scholar
• Horaud R, Conio B, Leboulleux O, et al. An analytic solution for the perspective 4-point problem. Comput Vision Graphics Image Process. 1989;1989(47):33–44.
   Google Scholar
• Haralick R, Lee C, Ottenberg K, et al. Review and analysis of solutions of the three point perspective pose estimation problem. Int J Comput Vision. 1994;13(3):331–356.
   Web of Science ®Google Scholar
• Quan L, Lan L. Linear n-point camera pose determination. IEEE Trans Pattern Anal Mach Intell. 1999;21(8):774–780.
   Web of Science ®Google Scholar
• Triggs B. Camera pose and calibration from 4 or 5 known 3D points. In: Proceedings of the Seventh IEEE International Conference on Computer Vision. Vol. 1999(1); Kerkyra, Greece; 1999. p. 278–284.
   Google Scholar
• Zhi L, Tang J. A complete linear 4-point algorithm for camera pose determinatio. MM Research Reprints. 2002;21:239–249.
   Google Scholar
• Hartley R, Zisserman A. Multiple view geometry in computer vision. Cambridge: Cambridge University Press; 2004; ISBN: 0521540518.
   Google Scholar
• Lepetit V, Pilet J, Fua P. Point matching as a classification problem for fast and robust object pose estimation. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol. 2004; Washington, DC; 2004. p. 244–250.
   Google Scholar
• Nister D. An efficient solution to the five-point relative pose problem. IEEE Trans Pattern Anal Mach Intell. 2004;26(6):756–777.
   PubMed Web of Science ®Google Scholar
• Mayer H. 3D reconstruction and visualization of urban scenes from uncalibrated wide-baseline image sequences. PFG Photogrammetrie -- Fernerkundung -- Geoinformation. 2007;2007(3):167–176.
   Google Scholar
• Pollefeys M, Nister D, Frahm J, et al. Detailed real-time urban 3D reconstruction from video. Int J Comput Vision. 2008;78(2–3):143–167.
   Web of Science ®Google Scholar
• Heinrichs M, Hellwich O, Rodehorst V. Robust spatio-temporal feature tracking. In: International Archives of Photogrammetry and Remote Sensing and Geospacial Science. Vol. 37/B3a; Beijing; 2008. p. 51–56.
   Google Scholar
• Reznik S, Mayer H. Implicit shape models, self-diagnosis, and model selection for 3D facade interpretation. PFG Photogrammetrie -- Fernerkundung -- Geoinformation. 2008;2008(3):187–196.
   Google Scholar
• Tuttas S, Stilla U. Reconstruction of façades in point clouds from multi aspect oblique als. ISPRS Ann Photogramm Remote Sens Spatial Inf Sci. 2013;2:91–96.
   Google Scholar
• Luhmann T, Ohm J, Piechel J, et al. Geometric calibration of thermographic cameras. Int Arch Photogramm Remote Sens Spatial Inf Sci. 2010;38(5):411–416.
   Google Scholar
• Laguela S, Gonzalez-Jorge H, Armesto J, et al. Calibration and verification of thermographic cameras for geometric measurements. Infrared Phys Technol. 2011;54:92–99.
   Web of Science ®Google Scholar
• St-Laurent L, Mikhnevich M, Bubel A, et al. Passive calibration board for alignment of vis-nir, swir and lwir images. Quant Infrared Thermograph J. 2017;14(2):193–205.
   Web of Science ®Google Scholar
• Hoegner L, Stilla U. Building facade object detection from terrestrial thermal infrared image sequences combining different views. ISPRS Ann Photogramm Remote Sens Spatial Inf Sci. 2015;II-3/W4:55–62.
   Google Scholar
• Westfeld P, Mader D, Maas H. Generation of TIR-attributed 3D point clouds from uav-based thermal imagery. PFG Photogrammetrie -- Fernerkundung -- Geoinformation. 2015;2015(5):381–394.
   Google Scholar
• Hoegner L, Hanel A, Weinmann M, et al. Towards people detection from fused time-of-flight and thermal infrared images. In: Photogrammetric Computer Vision 2014 - PCV2014. Vol. XL-3; Zurich; 2014. p. 121–126.
   Google Scholar
• Hoegner L, Kumke H, Meng L, et al. Automatic extraction of textures from infrared image sequences and database integration for 3D building models. PFG Photogrammetrie -- Fernerkundung -- Geoinformation. Hannover, 2007;2007(6):459–468.
   Google Scholar
• Stilla U, Kolecki J, Hoegner L. Texture mapping of 3D building models with oblique direct geo-referenced airborne ir image sequences. In: International Archives of Photogrammtry, Remote Sensing and Geospacial Sciences. Vol. 38; 2009.
   Google Scholar
• Iwaszczuk D, Hoegner L, Schmitt M, et al. Line based matching of uncertain 3D building models with IR image sequences for precise texture extraction. PFG Photogrammetrie -- Fernerkundung -- Geoinformation. 2012;2012(5):511–521.
   Google Scholar
• Michaelsen E, Iwaszczuk D, Sirmacek B, et al. Gestalt grouping on façade textures from IR image sequences: comparing different production systems. Int Arch Photogramm Remote Sens and Geospacial Sci. Melbourne, 2012;39:303–308.
   Google Scholar
• Hoegner L, Stilla U. Automatic generation of facade textures from terrestrial thermal infrared image sequences. In: Quantitative Infrared Termography - QIRT; 2014 Jul 07--12; Bordeaux; 2014.
   Google Scholar
• Hoegner L, Tuttas S, Xu Y, et al. Evaluation of methods for coregistration and fusion of rpas-based 3D point clouds and thermal infrared images. ISPRS - Int Arch Photogramm Remote Sens and Geospacial Sci. 2016;XLI-B3:241–246.
   Google Scholar
• Rusinkiewicz S, Levoy M. Effcient variants of the ICP algorithm. In: Proceedings of the IEEE 3rd International Conference on 3D Digital Imaging and Modeling; Los Alamitos; 2001. p. 145–152.
   Google Scholar
• Godding R. Camera calibration. In: Hornberg A, editor. Handbook of machine vision; Weinheim: Wiley-VCH; 2006. Chapter 5, p. 333–359.
   Google Scholar
• Hartley R. Lines and points in three views and the trifocal tensor. Int J Comput Vision. 1997;22(2):125–140.
   Web of Science ®Google Scholar
• Lowe D. Distinctive image features from scale-invariant keypoints. Int J Comput Vision. 2004;60(2):91–110.
   Web of Science ®Google Scholar
• Brown M, Lowe D. Automatic panoramic image stitching using invariant features. Int J Comput Vision. 2007;74(1):59–73.
   Web of Science ®Google Scholar
• Läbe T, Förstner W. Automatic relative orientation of images. In: Proceedings of the 5th Turkish-German Joint Geodetic Days. Vol. 2006; Berlin; 2006.
   Google Scholar
• Fischler M, Bolles R. Random sample consensus: A paradigm for model fit-ting with applications to image analysis and automated cartography. Commun ACM. 1981;24(6):381–395.
   Web of Science ®Google Scholar
• Hirschmueller H. Stereo processing by semiglobal matching and mutual information. IEEE Trans Pattern Anal Mach Intell. 2008;30(2):328–341.
   PubMed Web of Science ®Google Scholar
• Mayer H, Bartelsen J, Hirschmueller H, et al. Dense 3D reconstruction from wide baseline image sets. In: Dellaert F, Frahm JM, Pollefeys M, et al., editors. Outdoor and large-scale real-world scene analysis. 15th International Workshop on Theoretical Foundations of Computer Vision; 2011 Jun 26 -- Jul 1; Dagstuhl Castle, Germany. Vol. 7474. Springer: Berlin; 2012. p. 285–304.
   Google Scholar
• Förstner W, Gülch E. A fast operator for detection and precise location of distinct points, corners and centers of circular features. In: Proceedings of the ISPRS Intercommission Workshop on Fast Processing of Photogrammetric Data. Vol. 1987; Interlaken; 1987. p. 281–305.
   Google Scholar