14.5.7.1 Learning Model Descriptions

Chapter Contents (Back)
Model Based Vision. Learning Models.

Weng, J.Y.[Ju-Yang], Ahuja, N., Huang, T.S.,
Learning Recognition and Segmentation Using the Cresceptron,
IJCV(25), No. 2, November 1997, pp. 109-143.
DOI Link 9712
BibRef
Earlier:
Learning Recognition and Segmentation of 3-D Objects from 2-D Images,
ICCV93(121-128).
IEEE DOI The framework (called Cresceptron) to generalize models for recognition. The structures are the line segments that match the model. Illustrated on a number of different images. BibRef

Mirhosseini, A.R., Yan, H.,
Learning Object Models from Graph Templates,
JEI(6), No. 3, July 1997, pp. 294-302. 9807
BibRef

Wu, P.S.Y., Xiong, Y.G.,
A Learning Mechanism for Parts Recognition in an Intelligent Assembly System,
IJAMT(13), No. 6, 1997, pp. 413-418. 9708
BibRef

Caelli, T.M.[Terry M.], West, G.A.W.[Geoff A.W.], Robey, M.[Mike], Osman, E.[Erol],
A relational learning method for pattern and object recognition,
IVC(17), No. 5/6, April 1999, pp. 391-401.
Elsevier DOI BibRef 9904

Yeasin, M., Chaudhuri, S.,
Toward Automatic Robot Programming: Learning Human Skill from Visual Data,
SMC-B(30), No. 1, February 2000, pp. 180-184.
IEEE Top Reference. 0004
BibRef
Earlier:
Automatic Generation of Robot Program Code: Learning from Perceptual Data,
ICCV98(889-894).
IEEE DOI BibRef

Tamminen, T.[Toni], Lampinen, J.[Jouko],
Sequential Monte Carlo for Bayesian Matching of Objects with Occlusions,
PAMI(28), No. 6, June 2006, pp. 930-941.
IEEE DOI 0605
BibRef
Earlier:
A Bayesian Occlusion Model for Sequential Object Matching,
BMVC04(xx-yy).
HTML Version. 0508
BibRef
Earlier:
Learning an Object Model for Feature Matching in Clutter,
SCIA03(193-199).
Springer DOI 0310
BibRef

Kim, S.[Sungho], Yoon, K.J.[Kuk-Jin], Kweon, I.S.[In So],
Object Recognition Using a Generalized Robust Invariant Feature and Gestalt's Law of Proximity and Similarity,
PR(41), No. 2, February 2008, pp. 726-741.
Elsevier DOI 0711
BibRef PercOrg06(193).
IEEE DOI 0609
Background clutter; Interior context; Complementary feature; Contextual voting; Gestalt law BibRef

Kim, S.[Sungho], Kweon, I.S.[In So],
Biologically Motivated Perceptual Feature: Generalized Robust Invariant Feature,
ACCV06(II:305-314).
Springer DOI 0601
Combine radial symmetry and corner features. BibRef

Kim, S.[Sungho], Kweon, I.S.[In So],
Scalable representation for 3D object recognition using feature sharing and view clustering,
PR(41), No. 2, February 2008, pp. 754-773.
Elsevier DOI 0711
BibRef
Earlier:
Scalable Representation and Learning for 3D Object Recognition Using Shared Feature-Based View Clustering,
ACCV06(II:561-570).
Springer DOI 0601
3D object representation; Scalability; Robust invariant feature; Feature sharing; View clustering BibRef


Polak, S.[Simon], Shashua, A.[Amnon],
Latent Model Clustering and Applications to Visual Recognition,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Fidler, S.[Sanja], Berginc, G.[Gregor], Leonardis, A.[Ales],
Hierarchical Statistical Learning of Generic Parts of Object Structure,
CVPR06(I: 182-189).
IEEE DOI 0606
BibRef

Spence, C., Pearson, J.D., Sajda, P.,
Learning Hierarchical Representations of Objects,
ARPA96(1415-1428). BibRef 9600

Duric, Z., Rivlin, E., Rosenfeld, A.,
Learning an Object's Function by Observing the Object in Action,
ARPA96(1437-1446). BibRef 9600

Maloof, M.A.[Marcus A.], Langley, P.[Pat], Sage, S.[Stephanie], Binford, T.O.[Thomas O.],
Learning to Detect Rooftops in Aerial Images,
DARPA97(835-846). Cartography. BibRef 9700

Binford, T.O.[Thomas O.], and Levitt, T.S.[Tod S.], and Langley, P.[Pat],
Learning Object Models From Visual Observation and Background Knowledge,
ARPA94(I:765-772). BibRef 9400

Provan, G.M., Langley, P., Binford, T.O.,
Probabilistic Learning of Three-Dimensional Object Models,
ARPA96(1403-1414). BibRef 9600

Payne, J.[Janet], Day, M.[Mark],
A Projection Filter for Use with Parameterised Learning Models,
ICPR98(Vol I: 867-869).
IEEE DOI 9808
BibRef

Zhu, S.C., Mumford, D.,
Learning Generic Prior Models for Visual Computation,
CVPR97(463-469).
IEEE DOI 9704
Learning textures. BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Statistical Learning, Clustering, Learning Feature Values .


Last update:Mar 16, 2024 at 20:36:19