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taha.ridene@mines-paristech.fr

Robotics Lab, Mines ParisTech. «CO-REGISTRATION OF HETEREGENEOUS GEOREFERENCING 3D DATA : CONTRIBUTION OF MOBILE POINT CLOUDS CORRECTION ». Dr. Taha Ridene. taha.ridene@mines-paristech.fr. July 2010. Outlines. Introduction Rigid registration algorithms Results of registration Conclusion.

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taha.ridene@mines-paristech.fr

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  1. Robotics Lab, Mines ParisTech «CO-REGISTRATION OF HETEREGENEOUS GEOREFERENCING 3D DATA : CONTRIBUTION OF MOBILE POINT CLOUDS CORRECTION » Dr. TahaRidene taha.ridene@mines-paristech.fr July 2010

  2. Outlines • Introduction • Rigid registration algorithms • Results of registration • Conclusion taha.ridene@mines-paristech.fr 2/19

  3. 17 partners : 7 companies and 10 public research labs Digitalizing of the territories and their resources and exploitation of multimedia information Acquisition Data processing Introduction Rigid registration algorithms Results of registration Conclusion Global context • 3D Data sets Need for correction I. 3D data production II. Exploitation of 3D Video game Touristic Military GPS taha.ridene@mines-paristech.fr 3/19

  4. 17 partners : 7 companies and 10 public research labs Digitalizing of the territories and their resources and exploitation of multimedia information Acquisition Data processing To obtain a 3D mapping database : textured, triangulated and geo-referenced Introduction Rigid registration algorithms Results of registration Conclusion Global context • 3D Data sets Need for correction I. 3D data production Approach: 3D heteregenous representation fusion taha.ridene@mines-paristech.fr 4/19

  5. Introduction Rigid registration algorithms Results of registration Conclusion Global context • 3D Data sets Need for correction Mines ParisTech IGN Mensi Trimble taha.ridene@mines-paristech.fr 5/19

  6. Introduction Rigid registration algorithms Results of registration Conclusion Global context • 3D Data sets Need for correction 3D heteregenous data geo referenced in Lambert2 (1St initialization of the registration) Registration/correction Fusion Coherent datasets Data fusion layout taha.ridene@mines-paristech.fr 6/19

  7. Introduction Rigid registration algorithms Results of registration Conclusion Correction using DSM • ICP-SA R-ICP HPS-ICP Input 3D point clouds Portion of Interest 2 P3 P1 P2 1 T3 T1 T2 DSM P1ref Reference portion taha.ridene@mines-paristech.fr 7/19

  8. Pre-processing (s) Introduction Rigid registration algorithms Results of registration Conclusion M Q Correction using DSM • ICP-SA R-ICP Dynamic threshold HPS-ICP Q’ M’ Itératif step Least mean square (LMS) (William et al., 1988) Point to point Point to surface Top false true Convergence criteria KD-Tree acceleration (Mount and Sunil., 2006) (Ridene and Goulette, 2008, CTL 2009, RFPT 2010) taha.ridene@mines-paristech.fr 8/19

  9. Introduction Rigid registration algorithms Results of registration Conclusion Correction using DSM • ICP-SA R-ICP HPS-ICP Classical ICP-SA meet difficulty and fails Help the algorithm from the start taha.ridene@mines-paristech.fr 9/19

  10. K.N.N computing Introduction Rigid registration algorithms Results of registration Conclusion Correction using DSM • ICP-SA R-ICP HPS-ICP RANSAC (RANdom Sample Concensus) (Fischler and Bolles,1981) In registration (Chen et al., 1999; Bae and Lichti, 2008) M Q Initialisation by RANSAC ICP-SA (Ridene and Goulette, CIRA 2009) taha.ridene@mines-paristech.fr 10/19

  11. Horizontal plan extraction Apply T-init 2D projection Introduction Rigid registration algorithms Results of registration Conclusion Correction using DSM • ICP-SA R-ICP M Q HPS-ICP T2D estimation Tz estimation M’ Q’ Initialization by horizontal plan segmentation and registration ICP-SA (Jebbari et al, 2009) taha.ridene@mines-paristech.fr 11/19

  12. Horizontal plan extraction Apply T-init 2D projection Introduction Rigid registration algorithms Results of registration Conclusion Correction using DSM • ICP-SA R-ICP M Q HPS-ICP RANSAC Segmentation Algorithm Tz estimation T2D estimation « Profile-Based » segmentation 3D M’ Q’ 2D Initialization by horizontal plan segmentation and registration DoG Filter ICP-SA taha.ridene@mines-paristech.fr 12/19

  13. Horizontal plan extraction Apply T-init 2D projection Introduction Rigid registration algorithms Results of registration Conclusion Correction using DSM • ICP-SA R-ICP M Q HPS-ICP Tz estimation T2D estimation Q’ M’ Initialization by horizontal plan segmentation and registration ICP-SA taha.ridene@mines-paristech.fr 13/19

  14. Introduction Rigid registration algorithms Results of registration Conclusion Global results • Global performance taha.ridene@mines-paristech.fr 14/19

  15. Introduction Rigid registration algorithms Results of registration Conclusion Global results • Global performance Acceleration factor ~32 Traited area: ~ 5 millions of point Intel(R) Xeon (R) CPU 5130 @ 2.00GHZ avec 2Go de RAM Global time = 3 mn taha.ridene@mines-paristech.fr 15/19

  16. Introduction Rigid registration algorithms Results of registration Conclusion Rigid Registration : Possible solution for Mobile Mapping Systems geo-referencing/localization problems Correspondence after registration Shift problems taha.ridene@mines-paristech.fr 16/19

  17. Publications • Journals • T. Ridene and F. Goulette. Coregistration of DSM and 3D point cloudsacquired by a mobile mapping system. Geodetic sciences bulletin - Special Issue on Mobile MappingTechnology, 15(5) :824-838, 2009d. • T. Ridene and F. Goulette. Recalage de relevés laser fixes et mobiles sur MNS pour la cartographie numérique 3D. Revue Française de photogrammétrie et de télédétection, Jan. 2009a. • International conferences • T. Ridene and A. Manzanera. Mécanismes d’attention visuelle sur rétine artificielle. TAIMA’07., Hammamet, May. 2007. • T. Ridene and F. Goulette. Recalage hétérogène de données 3D d’environnements urbains. MajecSTIC’08 (IEEE France), Oct. 2008. • T. Ridene and F. Goulette. Recalage de relevés laser fixes et mobiles sur MNS pour cartographie numérique 3D. Colloque Techniques Laser Pour l’Etude des Environnements Naturels et Urbains, Jan. 2009. • T. Ridene and F. Nashashibi. Localisation précise d’un système de cartographie mobile pour la numérisation 3D d’environnement Urbain. ATEC-ITS, Feb. 2009. • T. Ridene and F. Goulette. Registration together and to DSM of several 3D point clouds issued from a Mobile Mapping System. Mobile Mapping Technologies, jul. 2009b. • T. Ridene and F. Goulette. Registration of fixed-and-mobile- based terrestrial laser data sets with DSM. pages 375-380, dec. 2009c. doi : 10.1109/CIRA.2009.5423176. • T. Ridene and F. Goulette. Feature-based quality evaluation of 3D heterogeneous data registration. In Proceedings of SPIE, volume 7526, page 75260Z, 2010. • T. Ridene and F. Goulette. USAGE DE LA CARTOGRAPHIE 3D POUR L’URBANISME ET LE SERVICE DE PROXIMITÉ -EXEMPLE D’APPLICATION AU DIAGNOSTIC D’ACCESSIBILITÉ. (Accepted) GEOTUNIS 2010 IJCV special ISSUE Sptember 2010 taha.ridene@mines-paristech.fr 17/19

  18. T H A N K Y O U F O R Y O U R A T T E N T I O N taha.ridene@mines-paristech.fr 18/19

  19. Introduction Rigid registration algorithms Results of registration Conclusion Global results • Global performance taha.ridene@mines-paristech.fr 14/19

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