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Automatic scan registration using 3D linear and planar features

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3D Research

Abstract

We present a common framework for accurate and automatic registration of two geometrically complex 3D range scans by using linear or planar features. The linear features of a range scan are extracted with an efficient split-and-merge line-fitting algorithm, which refines 2D edges extracted from the associated reflectance image considering the corresponding 3D depth information. The planar features are extracted employing a robust planar segmentation method, which partitions a range image into a set of planar patches. We propose an efficient probability-based RANSAC algorithm to automatically register two overlapping range scans. Our algorithm searches for matching pairs of linear (planar) features in the two range scans leading to good alignments. Line orientation (plane normal) angles and line (plane) distances formed by pairs of linear (planar) features are invariant with respect to the rigid transformation and are utilized to find candidate matches. To efficiently seek for candidate pairs and groups of matched features we build a fast search codebook. Given two sets of matched features, the rigid transformation between two scans is computed by using iterative linear optimization algorithms. The efficiency and accuracy of our registration algorithm were evaluated on several challenging range data sets.

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References

  1. D. Aiger, N. J. Mitra, D. Cohen-Or (2008) 4-Points Congruent Sets for Robust Pairwise Surface Registration, ACM SIGGRAPH

  2. S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, A. Y. Wu (1994) An Optimal Algorithm for Approximate Nearest Neighbor Searching in Fixed Dimensions, ACM-SIAM Symposium on discrete algorithms

  3. P. J. Besl, H. D. McKay (1992) A method for registration of 3-D shapes, IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2):239–256

    Article  Google Scholar 

  4. John Canny (1986) A Computational Approach to Edge Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(6):679–698

    Article  Google Scholar 

  5. C. Chao, I. Stamos (2006) Range Image Registration Based on Circular Features, The International Symposium on 3D Data Processing Visualization and Transmission

  6. C. Chao, I. Stamos (2005) Semi-automatic Range to Range Registration: a Feature-based Method, International Conference on 3-D Digital Imaging and Modeling (3DIM)

  7. Y. Chen, G. Medioni (1992) Object Modeling by Registration of Multiple Range Images, Image & Vision Computing, 10(3):145–155

    Article  Google Scholar 

  8. C. Dold, C. Brenner (2006) Registration of terrestrial laser scanning data using planar patches and image data, International Society for Photogrammetry and Remote Sensing

  9. D. Douglas, T. Peucker (1973) Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature, The Canadian Cartographer, 10(2):112–122

    Google Scholar 

  10. M. A. Fischler, R. C. Bolles (1987) Random Sample Consensus: a Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography, Communications of the ACM,:726–740

  11. M. Franaszek, G. S. Cheok, C. Witzgall (2009) Fast Automatic Registration of Range Images from 3D Imaging Systems Using Sphere Targets, Automation in Construction, 18(3):265–274

    Article  Google Scholar 

  12. N. Gelfand, N. J. Mitra, L. J. Guibas, H. Pottmann (2005) Robust Global Registration, Third Eurographics Symposium on Geometry Processing (SGP)

  13. F. Han, Z. W. Tu, S. C. Zhu (2004) Range Image Segmentation by an Effective Jump-Diffusion Method, IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(9):1138–1153

    Article  Google Scholar 

  14. R. I. Hartley, A. Zisserman (2004) Cambridge University Press, Multiple View Geometry in Computer Vision, ISBN: 0521540518, Second edition

  15. R. Hesami, A. Bab-Hadiashar, R. HosseinNezhad (2010) Range Segmentation of Large Building Exteriors: a Hierarchical Robust Approach, Computer Vision and Image Understanding, 114(4):475–490

    Article  Google Scholar 

  16. F. H. Daniel, M. Hebert (2003) Fully Automatic Registration of Multiple 3D Data Sets, Image and Vision Computing, 21(7):637–650

    Article  Google Scholar 

  17. A. E. Johnson, M. Hebert (1999) Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes, IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(5):433–449

    Article  Google Scholar 

  18. Joint Research Centre of European Commission, JRC 3D Reconstructor, http://www.reconstructor.it

  19. B. Kamgar-Parsi, B. Kamgar-Parsi (2004) Algorithms for Matching 3D Line Sets, IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(5):582–593

    Article  Google Scholar 

  20. Z. Z. Kang (2008) Automatic Registration of Terrestrial Point Cloud Using Panoramic Reflectance Images, International Society for Photogrammetry and Remote Sensing

  21. Kok-Lim Low (2004) Linear Least-Squares Optimization for Point-to-Plane ICP Surface Registration. Technical report, TR04-004, Department of Computer Science, University of North Carolina at Chapel Hill

  22. D. G. Lowe (2004) Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, 60(2):91–110

    Article  Google Scholar 

  23. A. Makadia, A. Patterson (2006) IV and Daniilidis, K. Fully Automatic Registration of 3D Point Clouds, IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  24. C. Matabosch, J. Salvi, D. Fofi, F. Meriaudeau (2005) Range image Registration for Industrial Inspection, Machine Vision Applications in Industrial Inspection XIII, pages 216–227

  25. V. Nguyen, S. Gächter, A. Martinelli, N. Tomatis, R. Siegwart (2007) A Comparison of Line Extraction Algorithms Using 2D Range Data for Indoor Mobile Robotics, Autonomous Robots, 23(2):97–111

    Article  Google Scholar 

  26. M. Pollefeys, L. Van Gool, M. Vergauwen, F. Verbiest, K. Cornelis, J. Tops, R. Koch (2004) Visual modeling with a hand-held camera, International Journal of Computer Vision, 59(3):207–232

    Article  Google Scholar 

  27. T. Rabbani, F. van den Heuvel (2005) Automatic Point Cloud Registration Using Constrained Search for Corresponding Objects, 7th Conference on Optical 3-D Measurement Techniques

  28. S. Rusinkiewicz, M. Levoy (2001) Efficient Variants of the ICP Algorithm, International Conference on 3-D Digital Imaging and Modeling (3DIM)

  29. A. Sampath, J. Shan (2010) Segmentation and Reconstruction of Polyhedral Building Roofs From Aerial Lidar Point Clouds, IEEE Transactions on Geoscience and Remote Sensing, 48(3):1554–1567

    Article  Google Scholar 

  30. I. Stamos, M. Leordeanu (2003) Automated Feature-based Range Registration of Urban Scenes of Large Scale, IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  31. Umeyama Shinji (1991) Least-Squares Estimation of Transformation Parameters Between Two Point Patterns, IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(4):376–380

    Article  Google Scholar 

  32. L. Wang, S. You, U. Neumann (2008) Supporting Range and Segment-based Hysteresis Thresholding in Edge Detection, International Conference on Pattern Recognition (ICIP)

  33. J. Yao, P. Taddei, M. R. Ruggeri, V. Sequeira (2010) Complex and Photo-realistic Scene Representation Based on Range Planar Segmentation and Model Fusion, The International Journal of Robotics Research, submitted

  34. Jian Yao (2006) PhD thesis, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, P.R. China, Modeling and rendering from multiple views, Adviser-Cham, Wai-Kuen

    Google Scholar 

  35. Jian Yao, Cham, Wai-Kuen (2007) Robust multi-view Feature Matching from Multiple Unordered Views, Pattern Recognition, 40(11):3081–3099

    Article  MATH  Google Scholar 

  36. L. Yu, D. Zhang, E. Holden (2008) A Fast and Fully Automatic Registration Approach Based on Point Features for Multi-source Remote-sensing Images, Computers and Geosciences, 34(7):838–848

    Article  Google Scholar 

  37. A. Zaharescu, E. Boyer, K. Varanasi, R. Horaud (2009) Surface Feature Detection and Description with Applications to Mesh Matching, IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  38. Wei Zhang, Jian Yao, Wai-Kuen Cham (2010) 3D Modeling from Multiple Images, The Seventh International Symposium on Neural Networks (ISNN 2010), pages 97–103

  39. Z. Zhang, O. D. Faugeras (1991) Determining motion from 3D line segment matches: a comparative study, Image Vision Computing, 9(1):10–19

    Article  Google Scholar 

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Authors and Affiliations

  1. Institute for the Protection and Security of the Citizen (IPSC) European Commission, Joint Research Centre (JRC), Ispra, Italy

    Jian Yao, Mauro R. Ruggeri, Pierluigi Taddei & Vítor Sequeira

Authors
  1. Jian Yao
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  2. Mauro R. Ruggeri
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  3. Pierluigi Taddei
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  4. Vítor Sequeira
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Correspondence to Jian Yao.

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Yao, J., Ruggeri, M.R., Taddei, P. et al. Automatic scan registration using 3D linear and planar features. 3D Res 1, 6 (2010). https://doi.org/10.1007/3DRes.03(2010)06

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  • DOI: https://doi.org/10.1007/3DRes.03(2010)06

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