N3M: Natural 3D markers for real-time object detection and pose estimation

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2007, Pages

  Hinterstoisser, Stefan ^a   Benhimane, Selim ^a   Navab, Nassir ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER NETWORKS; COMPUTER VISION; FEATURE EXTRACTION; PHOTOLITHOGRAPHY;

OBJECT DETECTION; POSE-ESTIMATION;

COMPUTER APPLICATIONS;

EID: 50649095430     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2007.4409004     Document Type: Conference Paper

References (27)

1. H. Bay, T. Tuytelaars, and L. V. Gool. Surf: Speeded up robust features. European Conf. on Computer Vision, 2006.
2. J. F. Canny. A computational approach to edge detection. IEEE Trans. on Pattern Analysis and Machine Intelligence, 8(6):679-698, 1986.
3. B. Espiau, F. Chaumette, and P. Rives. A new approach to visual servoing in robotics. IEEE Trans. on Robotics and Automation, 8(3):313-326, 1992.
4. M. Fiala. Artag, a fiducial marker system using digital techniques. In IEEE Conf. on Computer Vision and Pattern Recognition, pages 590-596, 2005.
5. M. Fischler and R. Bolles. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM, 24(6):381-395, 1981.
6. W. Forstner. A framework for low-level feature extraction. In European Conf. on Computer Vision, pages 383-394, 1994.
7. C. Harris and M. Stephens. A combined corner and edge detector. In Proc. of the 4th Alvey Vision Conf., pages 147-151, 1988.
8. T. Kadir, A. Zisserman, and M. Brady. An affine invariant salient region detector. European Conf. on Computer Vision, 2004.
9. H. Kato and M. Billinghurst. Marker tracking and hmd calibration for a video-based augmented reality conferencing system. In Proc. of the 2nd Int. Workshop on Augmented Reality, 1999.
10. Y. Lambdan and H. Wolfson. Geometric hashing: A general and efficient model-based recognition scheme. IEEE Int. Conf. on Computer Vision, pages 238-249, 1988.
11. V. Lepetit and P. Fua. Keypoint recognition using randomized trees. In IEEE Trans. on Pattern Analysis and Machine Intelligence, 2006.
12. D. Lowe. Distinctive image features from scale-invariant keypoints. Int. Journal of Computer Vision, 60(2):91-110, 2004.
13. E. Malis, F. Chaumette, and S. Boudet. 2 1/2 d visual servoing. IEEE Trans. on Robotics and Automation, 15(2):234-246, 1999.
14. J. Matas, O. Chum, M. Urban, and T. Pajdla. Robust wide baseline stereo from maximally stable extremal regions. British Machine Vision Conf., 2002.
15. K. Mikolajczyk and C. Schmid. Scale & affine invariant interest point detectors. Int. Journal of Computer Vision, 60(1):63-86, 2004.
16. H. Najafi, Y. Genc, and N. Navab. Fusion of 3d and appearance models for fast object detection and pose estimation. IEEE Asian Conf. on Computer Vision, pages 415-426, 2006.
17. M. Özuysal, V. Lepetit, F. Fleuret, and P. Fua. Feature harvesting for tracking-by-detection. eccv, pages 592-605, 2006.
18. P. Pritchett and A. Zisserman. Wide baseline stereo matching. In IEEE Int. Conf. on Computer Vision, pages 754-760, 1998.
19. R.Fergus, L.Fei-Fei, P.Perona, and A.Zisserman. Learning object categories from google's image search. IEEE Int. Conf. on Computer Vision, 2005.
20. C. Schmid and R. Mohr. Local grayvalue invariants for image. IEEE Trans. on Pattern Analysis and Machine Intelligence, 19(5):530-535, 1997.
21. C. Schmid, R. Mohr, and C. Bauckhage. Evaluation of interest point detectors. Int. Journal of Computer Vision, 37(2):151-172, 2000.
22. J. Sivic and A. Zisserman. Video google: A text retrieval approach to object matching in videos. IEEE Int. Conf. on Computer Vision, 2003.
23. S. M. Smith and J. M. Brady. Susan - a new approach to low level image processing. Int. Journal of Computer Vision, 23:45-78, 1997.
24. C. Steger. Similarity measures for occlusion, clutter, and illumination invariant object recognition. In B. Radig and S. Florczyk, editors, Pattern Recognition, volume 2191 of Lecture Notes in Computer Science, pages 148-154, Berlin, 2001. Springer-Verlag.
25. R. Tsai. A versatile camera calibration technique for high-accuracy 3d machine vision metrology using off-the-shelf tv cameras and lenses. IEEE Journal of Robotics and Automation, 3(4):323-344, 1987.
26. T. Tuytelaars and L. van Gool. Matching Widely Separated Views Based on Affine Invariant Regions. Kluwer Academic Publishers, 2004.
27. Z. Zhang, R. Deriche, O. Faugeras, and Q.-T. Luong. A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry. Technical Report 2273, INRIA, 1994.