2D-3D feature extraction and registration of real world scenes

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 36, Issue , 2006, Pages 32-37

  Alshawabkeh, Yahya ^a   Haala, Norbert ^a   Fritsch, Dieter ^a  

^a UNIVERSITY OF STUTTGART   (Germany)

Author keywords

Cultural Heritage; Laser Scanner; Photogrammetry; Registration; Segmentation; Texture Mapping

Indexed keywords

COMPUTATIONAL EFFICIENCY; EXTRACTION; FEATURE EXTRACTION; IMAGE SEGMENTATION; MAPPING; PHOTOGRAMMETRY;

CULTURAL HERITAGES; EDGE DETECTION ALGORITHMS; GEOMETRIC MODELING; LASER SCANNER; RANGE IMAGE SEGMENTATION; REGISTRATION; ROBUSTNESS AGAINST NOISE; TEXTURE MAPPING;

EDGE DETECTION;

EID: 85015538116     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (28)

1. Alshawabkeh, Y. & Haala N. [2005], Automatic Multi-Image Photo Texturing of Complex 3D Scenes. CIPA IAPRS Vol. 34-5/C34, pp. 68-73.
2. Besl, P. & Jain, R. [1988], Segmentation Through Variable-Order Surface Fitting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 9(2): 167-192.
3. Boehler, W., Marbs, A., 2002. 3D scanning instruments. ISPRS/CIPA International Workshop on Scanning for Cultural Heritage Recording, Corfu, Greece, pp.9-12.
4. Bruni, V., Vitulano, D. & Maniscalco,U. [2004], Fast Segmentation and Modeling of Range Data Via Steerable Pyramid and Superquadrics. The 12-th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision'2004, WSCG 2004, University of West Bohemia, Czech Republic.
5. Canny, J. [1986], A Computational Approach to Edge Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 8, No. 6, Nov.
6. Christy, S. & Horaud, R. [1996], Iterative Pose Computation from Line Correspondences. Computer Vision and Image Understanding Vol. 73, No. 1, January, pp. 137-144.
7. Djebali, M., Melkemi, M. & Sapidis, N. [2002], "Range-Image Segmentation and Model Reconstruction Based on a Fit-and-Merge Strategy," ACM Symposium on Solid Modeling and Applications, pp.127-138.
8. El-Hakim, S., Beraldin, A. & Picard, M. [2002], Detailed 3D reconstruction of monuments using multiple techniques. ISPRS /CIPA .Corfu, Greece, pp.58-64.
9. Ferencz, A. [2001], Texture Mapping Range Images. Masters Thesis, Computer Science Division, EECS, UC Berkeley.
10. Gächter, S. [2005], Results on range image segmentation for service robots. Technical Report. Switzerland.
11. Han, F., Tu, Z. & Zhu, S. [2004], Range image segmentation by an efficient jump-diffusion method. In IEEE Trans. On Pattern Analysis and Machine Intelligence.Vol.26/9. pp.1138-1153.
12. Haralick, R., Lee, C., Ottenberg, K. & Nolle, M. [1994], Review and analysis of solutions of the 3-point perspective pose estimation problem. IJCV 13(3), pp. 331-356.
13. Horaud, R., Dornaika, F., Lamiroy, B. & Christy, S. [1997], “Object pose: The link between weak perspective, paraperspective, and full perspective,” Int. J. Comput. Vision, vol. 22, no. 2, pp. 173-189.
14. Hoover, A., Jean-Baptiste, G. & Jiang, X. [1996], An Experimental Comparison of Range Image Segmentation Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(7): p. 673-689.
15. Jiang, X. & Bunke, H. [1999], Edge detection in range images based on scan line approximation. Computer Vision and Image Understanding: CVIU, 73(2): 183-199.
16. Katsoulas, D. & Werber, A. [2004], Edge Detection in Range Images of Piled Box-like Objects. 17th International
17. Conference on Pattern Recognition (ICPR 2004), 4-Volume Set, Cambridge, UK. IEEE Computer Society, ISBN 0-7695-2128-2.pp 80-84.
18. Klinec, D. & Fritsch, D. [2003], Towards pedestrian navigation and orientation. Proceedings of the 7th South East Asian Survey Congress: SEASC'03, Hong Kong, November 3-7.
19. Lee, Y. & Habib, A. [2002], Pose Estimation of Line Cameras Using Linear Features, ISPRS Symposium of PCV'02 Photogrammetric Computer Vision, Graz, Austria.
20. Lensch, H., Heidrich, W. & Seidel, H. [2000], Automated texture registration and stitching for real world models. In Proceedings of Pacific Graphics 2000, pages 317-326.
21. Liu, L. & Stamos, S. [2005], Automatic 3D to 2D registration for the photorealistic rendering of urban scenes. Computer Vision and Pattern Recognition. IEEE Computer Society.
22. Marshall, D., Lukacs, G. & Martin, R. [2001], Robust segmentation of primitives from range data in the presence of geometric degeneracy; IEEE Trans. Pattern Analysis and Machine Intelligence 23(3), 304-314.
23. Ohio State University range Image Collection, http://sampl.ece.ohio-state.edu/data/.
24. Palmer, P., Dabis, H. & Kittler, J. [1996] A performance measure for boundary detection algorithms. CVGIP: Image Understanding, 63(3): 476-494.
25. Sappa, A. & Devy, M. [2001], “Fast Range Image Segmentation by an Edge Detection Strategy,” Proc. IEEE Conf. 3D Digital Imaging and Modeling, pp. 292-299.
26. Sze, C., Liao, H., Hung, H., Fan, K. & Hsieh, J. [1998], “Multiscale edge detection on range images via normal changes,” IEEE Transition. Circuits System. II, vol. 45, pp. 1087-1092.
27. Yu, Y., & Ferencz, A., [2001] Extracting Objects from Range and Radiance Images. IEEE Transactions on Visualization and Computer Graphics, Vol /, No.4.
28. Yu, Y., Ferencz, A. & Malik,J. [2000] Compressing Texture Maps for Large Real Environments. SIGRAPH'2000.