OBLIQUE MULTI-CAMERA SYSTEMS - ORIENTATION AND DENSE MATCHING ISSUES

The use of oblique imagery has become a standard for many civil and mapping applications, thanks to the development of airborne digital multi-camera systems, as proposed by many companies (Blomoblique, IGI, Leica, Midas, Pictometry, Vexcel/Microsoft, VisionMap, etc.). The indisputable virtue of oblique photography lies in its simplicity of interpretation and understanding for inexperienced users allowing their use of oblique images in very different applications, such as building detection and reconstruction, building structural damage classification, road land updating and administration services, etc. The paper reports an overview of the actual oblique commercial systems and presents a workflow for the automated orientation and dense matching of large image blocks. Perspectives, potentialities, pitfalls and suggestions for achieving satisfactory results are given. Tests performed on two datasets acquired with two multi-camera systems over urban areas are also reported.

[1]  R. Reulke,et al.  Remote Sensing and Spatial Information Sciences , 2005 .

[2]  Li Zhang.  Automatic Digital Surface Model (DSM) generation from linear array images , 2005 .

[3]  M. Pierrot-Deseilligny,et al.  A MULTIRESOLUTION AND OPTIMIZATION-BASED IMAGE MATCHING APPROACH : AN APPLICATION TO SURFACE RECONSTRUCTION FROM SPOT 5-HRS STEREO IMAGERY , 2006 .

[4]  Olivier D. Faugeras,et al.  Multi-View Stereo Reconstruction and Scene Flow Estimation with a Global Image-Based Matching Score , 2007, International Journal of Computer Vision.

[5]  C. Lemmen,et al.  Pictometry : potentials for land administration , 2007 .

[6]  P. Reinartz,et al.  Calibration of a Wide-Angel Digital Camera System for Near Real Time Scenarios , 2007 .

[7]  F. Kurza,et al.  CALIBRATION OF A WIDE-ANGLE DIGITAL CAMERA SYSTEM FOR NEAR REAL TIME SCENARIOS , 2007 .

[8]  H. Hirschmüller.  Ieee Transactions on Pattern Analysis and Machine Intelligence 1 Stereo Processing by Semi-global Matching and Mutual Information , 2022 .

[9]  Görres Grenzdörffer,et al.  Photogrammetric image acquisition and image analysis of oblique imagery , 2008 .

[10]  H. Hirschmüller.  Stereo Processing by Semiglobal Matching and Mutual Information , 2008, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Eyal Ofek,et al.  Validation of vector data using oblique images , 2008, GIS '08.

[12]  K. Jacobsen.  Geometry of vertical and oblique image combinations , 2008 .

[13]  Yandong Wang,et al.  PICTOMETRY ' S PROPRIETARY AIRBORNE DIGITAL IMAGING SYSTEM AND ITS APPLICATION IN 3 D CITY MODELLING , 2008 .

[14]  Armin Gruen,et al.  Turning Images into 3-D Models ( Developments and performance analysis of image matching for detailed surface reconstruction of heritage objects ) , 2008 .

[15]  M. Gerke.  Dense matching in high resolution oblique airborne images , 2009 .

[16]  A. P. Nyaruhuma,et al.  Incorporating scene constraints into the triangulation of airborne oblique images , 2009 .

[17]  Dima Damen,et al.  Recognizing linked events: Searching the space of feasible explanations , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[18]  Jean Ponce,et al.  Accurate, Dense, and Robust Multiview Stereopsis , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  Richard Szeliski,et al.  Towards Internet-scale multi-view stereo , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[20]  Fabio Remondino,et al.  Orientation and 3D modelling from markerless terrestrial images: combining accuracy with automation , 2010 .

[21]  M. Kheiri.  DIGITAL AERIAL CAMERAS , 2010 .

[22]  George Vosselman,et al.  Building extraction from oblique airborne imagery based on robust façade detection , 2012 .

[23]  J. Moré,et al.  ORIENTATION STRATEGIES FOR AERIAL OBLIQUE IMAGES , 2012 .

[24]  Dieter Fritsch,et al.  Towards All-in-one Photogrammetry , 2012 .

[25]  Fabio Remondino,et al.  AUTOMATED AND ACCURATE ORIENTATION OF COMPLEX IMAGE SEQUENCES , 2012 .

[26]  M. Pierrot Deseilligny,et al.  APERO, AN OPEN SOURCE BUNDLE ADJUSMENT SOFTWARE FOR AUTOMATIC CALIBRATION AND ORIENTATION OF SET OF IMAGES , 2012 .

[27]  Norbert Haala,et al.  Dense Multi-Stereo Matching for High Quality Digital Elevation Models , 2012 .

[28]  M. Rothermel,et al.  Oblique Image Data Processing – Potential , Experiences and Recommendations , 2013 .

[29]  VisionMap Sensors and Processing Roadmap , 2013 .

[30]  Fabio Remondino,et al.  Building Footprints Extraction from Oblique Imagery , 2013 .

[31]  Markus Gerke,et al.  Supervised and unsupervised MRF based 3D scene classification in multiple view airborne oblique images , 2013 .

[32]  N. Haala.  The Landscape of Dense Image Matching Algorithms , 2013 .

[33]  Erica Nocerino,et al.  Dense image matching: Comparisons and analyses , 2013, 2013 Digital Heritage International Congress (DigitalHeritage).

[34]  Fabio Remondino,et al.  AUTOMATIC ORIENTATION OF LARGE BLOCKS OF OBLIQUE IMAGES , 2013 .