Abstract
We present an approach general enough to apply to recognition of complex rigid 3D objects from either a single intensity image or a single range image. Within the general paradigm of recognition by alignment, we address (1) definition and detection of primitives, (2) indexing to model hypotheses, (3) constructing view sphere models from sensed data, and (4) aligning model and sensed features for verification. The overall paradigm is not new, but rather fits within theory already espoused by Lowe and Ullman and many others: our position is therefore both a synthesis of and endorsement of much other work toward recognition of rigid free-form objects.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
R. Bajcsy and F. Solina: Three-Dimensional Object representation Revisited. Proceedings 1st Int. Conf. on Computer Vision, (1987) 231–240
R. Basri and S. Ullman: The Alignment of Objects with Smooth Surfaces. Proceedings 2nd Int. Conf. on Computer Vision, (1988) 482–488
K. Bowyer, D. Eggert, J. Stewman, and L. Stark: Developing the Aspect Graph Representation for Use in Image Understanding. In Proc. DARPA Image Understanding Workshop, Palo Alto,(1989) 831–849
T. Breuel: Adaptive Model-based Indexing. In Proc. 1989 DARPA Image Understanding Workshop, (1989) 805–814
A. Califano and R. Mohan: Multidimensional Indexing for Recognizing Visual Shapes. IEEE T-PAMI, Vol 16., No. 4, (1994) 373–392
S.-W. Chen: Wing Representation for Rigid 3D Objects. In Proc. 10th IAPR, Atlantic City, NJ, (June 1990) 398–402
J.-L. Chen, G. Stockman, and K. Rao: Recovering and Tracking Pose of Curved 3D Objects from 2D Images. Proc. IEEE Conf. on Computer Vision and Pattern Recognition, New York, NY, (June 1993) 233–239
J.-L. Chen and G. Stockman: Indexing to model aspects using invariant contour features. Computer Science Dept. Tech. Rep., Michigan State Univ., (Nov 1994)
J. Ponce, D. Forsyth, L. Shapiro, R. Bajcsy, D. Metaxas, M. Hebert, K. Ikeuchi, S. Sclaroff, A. Pentland, T. Binford, A. Kak, and G. Stockman: Object Representation for Object Recognition. Proc. IEEE Conf. on Computer Vision and Pattern Recognition, Seattle, WA, (June 1994) 147–152
S. Edelman and D. Weinshall: A Self-organizing Multiple View Representation of 3D Objects: Biological Cybernetics, Vol.64, (1991) 209–219
P. J. Flynn and A. K. Jain: BONSAI: 3D object recognition using constrained search: IEEE-T-PAMI, Vol. 13, No. 10, (Oct 1991) 1066–1075
C. Goad: Special Purpose Automatic Programming for 3D Model-based Vision. In Proc. DARPA Image Understanding Workshop, Arlington, VA, (1983)
D. D. Hoffman and W. A. Richards: Representing smooth plane curves for recognition. In Proc. AAAI, Pittsburg,PA (1982) 5–8
D. Huttenlocher and S. Ullman: Recognizing solid objects using alignment: Proc. DARPA Image Understanding Workshop, (April 1988) 1114–1122
K. Higuchi, H. Delingette, M. Hebert, and K. Ikeuchi: Merging Multiple Views Using a Spherical Representation. In Proc. IEEE 2nd CAD-Based Vision Workshop, Champion, PA (Feb 1994) 124–131
G. C. Lee: Scene Representation from Fused Imagery. PhD Dissertation, Michigan State Univ., (August 1992)
D. G. Lowe: Three-dimensional Object Recognition from Single Two-dimensional Images. Artificial Intelligence, Vol.31 No.3, (1987) 355–395
A. Pentland, B. Moghaddam, and T. Starner: View-Based and Modular Eigenspaces for Face Recognition. Proceedings IEEE Conf. on Computer Vision and Pattern Recognition, Seattle, WA, (June 1994) 84–91
P. L. Rosin: Multiscale Representation and Matching of Curves Using Codons. CVGIP: Graphical Models and Image Proc., Vol. 55, No. 4, (1993) 286–310
G. Stockman: Object Recognition and Localization via Pose Clustering. CVGIP, Vol. 40, (1987) 361–387
G. Taubin and F. Cukierman and S. Sullivan and J. Ponce and D. J. Kriegman: Parameterized Families of Polynomials for Bounded Algebraic Curve and Surface Fitting. IEEE T-PAMI, vol.16 no.3, (Mar 1994) 287–303
S. Ullman: An Approach to Object Recognition: Aligning Pictorial Descriptions. Technical Report AI Memo No.931, M.I.T. AI Laboratory, (1986)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1995 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Stockman, G. (1995). Object representation for recognition-by-alignment. In: Hebert, M., Ponce, J., Boult, T., Gross, A. (eds) Object Representation in Computer Vision. ORCV 1994. Lecture Notes in Computer Science, vol 994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60477-4_5
Download citation
DOI: https://doi.org/10.1007/3-540-60477-4_5
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-60477-8
Online ISBN: 978-3-540-47526-2
eBook Packages: Springer Book Archive