Abstract
We evaluate the power of 3D affine invariants in an object recognition scheme. These invariants are actively estimated by Kalman filtering the data obtained from real-time tracking of image features through a sequence of images. Object information is stored and retrieved in a hash table using the invariants as stable indices. Recognition takes place when significant evidence for a particular shape has been found from the table. Results with real data are presented, and the noise problems arising due to the weak perspective approximation and corner localisation errors are discussed. Preliminary results for extending this method to multiple object recognition in cluttered scenes are also presented.
Chapter PDF
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
R.T. Chin and C.R. Dyer. Model-Based Recognition in Robot Vision. ACM Computing Surveys, 18(1):67–108, 1986.
D.G. Lowe. The viewpoint consistency constraint. Int. Journal of Computer Vision, 1:57–72, 1987.
D.P. Huttenlocher and S. Ullman. Recognising solid objects by alignment with an image. Int. Journal of Computer Vision, 5(2):195–212, 1990.
W.E.L. Grimson and T. Lozano-Perez. Localising Overlapping Parts by Searching the Interpretation Tree. IEEE Trans. Pattern Analysis and Machine Intell., 9(4):469–482, 1987.
J.L. Mundy and A.Zissermann editors. Geometric Invariance in Computer Vision. MIT Press, 1992.
L.G. Roberts. Machine perception of three — dimensional solids. In J.T. Tippet, editor, Optical and Electro-optical Information Processing. MIT Press, 1965.
J.J. Koenderink and A.J. van Doorn. Affine structure from motion. J. Opt. Soc. America, 8(2):377–385, 1991.
D. Weinshall. Model-Based Invariants for 3-D Vision. Int. Journal of Computer Vision, 10(1):27–42, 1993.
J. B. Burns, R. S. Weiss, and E. M. Riseman. View variation of point-set and line-segment features. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(1):51–68, January 1993.
R. Fawcett, A. Zisserman, and M. Brady. Extracting structure from an affine view of a 3D point set with one or two bilateral symmetries. In Proceedings of the British Machine Vision Conference, pages 349–358, Guildford, 1993.
S. Vinther and R. Cipolla. Towards 3D object model acquisition and recognition using 3D affine invariants. In Proc. British Machine Vision Conference 1993, pages 369–378, 1993.
S. Vinther and R. Cipolla. Active 3D object recognition using 3D affine invariants. Technical Report CUED/F-INFENG/TR164, Dept. of Engineering, University of Cambridge, 1994.
Y. Lamdan, J.T. Schwartz, and H.J. Wolfson. Affine Invariant Model-Based Object Recognition. IEEE Trans. on Robotics and Automation, 6(5):578–589, 1990.
W.E. Grimson, D.P. Huttenlocher, and D. Jacobs. A study of affine matching with bounded sensor error. In Proc. 2rd European Conf. on Computer Vision, 1992.
D.G. Lowe. Three dimensional object recognition from single two-dimensional images. Artificial Intelligence, 31:355–395, 1987.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1994 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Vinther, S., Cipolla, R. (1994). Active 3D object recognition using 3D affine invariants. In: Eklundh, JO. (eds) Computer Vision — ECCV '94. ECCV 1994. Lecture Notes in Computer Science, vol 801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0028331
Download citation
DOI: https://doi.org/10.1007/BFb0028331
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-57957-1
Online ISBN: 978-3-540-48400-4
eBook Packages: Springer Book Archive