Matching of 3D building models with IR images for texture extraction

Thermal inspections of buildings contribute to detection of damaged and weak spots in the building hull. 3D spatial reference for this purpose can be achieved combining infrared images with 3D building models via texture mapping. Using terrestrial image sequences from a camera mounted in a mobile platform frontal faces can be captured, while airborne image sequences can be taken for roofs and inner yards. However, according to different geometry of acquisition, two different methods for matching of terrestrial and airborne images are required. In this paper we present a concept for texturing of an existing 3D building model with complementary terrestrial and airborne IR image sequences. First we present a method for matching of terrestrial image sequences based on relative orientation of the point cloud. Second, we introduce a method for matching of airborne images including system calibration and best texture selection. Further, the combination of the terrestrial and airborne data in one 3D building model is introduced.

[1]  Jan-Michael Frahm,et al.  Detailed Real-Time Urban 3D Reconstruction from Video , 2007, International Journal of Computer Vision.

[2]  W. Förstner.  OPTIMAL VANISHING POINT DETECTION AND ROTATION ESTIMATION OF SINGLE IMAGES FROM A LEGOLAND SCENE , 2010 .

[3]  Uwe Soergel,et al.  GENERATION OF 3D-CITY MODELS AND THEIR UTILISATION IN IMAGE SEQUENCES , 2000 .

[4]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[5]  Jan Skaloud,et al.  Theory and reality of direct georeferencing in national coordinates , 2008 .

[6]  Avideh Zakhor,et al.  Automatic registration of aerial imagery with untextured 3D LiDAR models , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[7]  Uwe Stilla,et al.  CALIBRATION OF AN IR CAMERA SYSTEM FOR AUTOMATIC TEXTURING OF 3D BUILDING MODELS BY DIRECT GEO-REFER , 2009 .

[8]  Christian Früh,et al.  Automated texture mapping of 3D city models with oblique aerial imagery , 2004, Proceedings. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004..

[9]  K. Jacobsen,et al.  Direct Sensor Orientation for Large Scale Mapping—Potential, Problems, Solutions , 2005 .

[10]  Liang-Tien Chia,et al.  Estimating camera pose from a single urban ground-view omnidirectional image and a 2D building outline map , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[11]  V. Rodehorst,et al.  ROBUST SPATIO-TEMPORAL FEATURE TRACKING , 2008 .

[12]  Helmut Mayer.  3D Reconstruction and Visualization of Urban Scenes from Uncalibrated Wide-Baseline Image Sequences , 2008 .

[13]  David Nistér,et al.  An efficient solution to the five-point relative pose problem , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[14]  Michael Cramer,et al.  Experiences on operational GPS/inertial system calibration in airborne photogrammetry 1 , 2002 .