12.1.7 Principal Component Decompositions, Point features

Chapter Contents (Back)
Matching, Invariants. Eigen Representations. Invariants. Filters for Matching. See also Recognition and Analysis of Faces.

Caelli, T.M.[Terry M.], Bischof, W.F.[Walter F.], Liu, Z.Q.[Zhi-Qiang],
Filter-Based Models for Pattern Classification,
PR(21), No. 6, 1988, pp. 639-650.
Elsevier DOI BibRef 8800

Zetzsche, C., Caelli, T.M.,
Invariant Pattern Recognition Using Multiple Filter Image Representations,
CVGIP(45), No. 2, February 1989, pp. 251-262.
Elsevier DOI BibRef 8902

Xu, J., Yang, Y.H.,
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PRL(7), 1988, pp. 191-197. BibRef 8800

de Bougrenet de la Tocnaye, J.L., Ghorbel, F.,
Scale-Rotation Invariant Pattern Recognition Applied to Image Data Compression,
PRL(8), 1988, pp. 55-58. BibRef 8800

Wu, X.[Xing], Bhanu, B.[Bir],
Gabor Wavelet Representation for 3-D Object Recognition,
IP(6), No. 1, January 1997, pp. 47-64.
Gabor Wavelets for 3-D Object Recognition,

Rao, R.P.N.[Rajesh P.N.], Ballard, D.H.[Dana H.],
Dynamic-Model of Visual Recognition Predicts Neural Response Properties in the Visual-Cortex,
NeurComp(9), No. 4, May 15 1997, pp. 721-763. 9706

PS File. BibRef

Ballard, D.H., Rao, R.P.N.,
Seeing Behind Occlusions,
Springer DOI BibRef 9400
And: Univ. of RochesterURCSD-94-487, February 1994. BibRef

Rao, R.P.N.[Rajesh P.N.], Ballard, D.H.[Dana H.],
Object Indexing Using an Iconic Sparse Distributed Memory,
IEEE DOI Use an "Eigen" representation of the data and match these values.
PS File. BibRef 9500

Rao, R.P.N.[Rajesh P.N.], Ballard, D.H.[Dana H.],
Natural Basis Functions and Topographic Memory for Face Recognition,
PS File. BibRef 9500

Rao, R.P.N.[Rajesh P.N.], Ballard, D.H.[Dana H.],
Localized Receptive Fields May Mediate Transformation-Invariant Recognition in the Visual Cortex,
Univ. of Rochester97.2, May 1997.
PS File. BibRef 9705

Rao, R.P.N.[Rajesh P.N.], Ballard, D.H.[Dana H.],
A Class of Stochastic Models for Invariant Recognition, Motion, and Stereo,
Univ. of RochesterURCSD-96-1, 1996.
PS File. BibRef 9600

Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
2-D Points with 3-D Structures .

Last update:Aug 16, 2018 at 18:22:30