13.1.3.1 Pose Estimation, 3D Models

Chapter Contents (Back)
Matching, Pose. Matching, Volumes. Matching, Accumulation. Hough. Pose Estimation, Accumulation. Pose Estimation, Hough.

Peek, S.A., Mayhew, J.E.W., Frisby, J.P.,
Obtaining Viewing Distance and Angle of Gaze from Vertical Disparity Using a Hough-Type Accumulator,
IVC(2), No. 4, November 1984, pp. 180-190.
Elsevier DOI BibRef 8411

Dhome, M., and Kasvand, T.,
Polyhedron Recognition by Hypothesis Accumulation,
PAMI(9), No. 3, May 1987, pp. 429-438. BibRef 8705
Earlier:
Hierarchical Approach for Polyhedra Recognition by Hypothesis Accumulation,
ICPR86(88-91). BibRef

Stockman, G.C.[George C.],
Object Recognition and Localization via Pose Clustering,
CVGIP(40), No. 3, December 1987, pp. 361-387.
Elsevier DOI Recognize Three-Dimensional Objects. This is a follow-on paper to the next one, but discusses the general technique in terms of pose clustering. BibRef 8712

Stockman, G.C.[George C.],
Object Representation for Recognition-by-Alignment,
ORCV94(77-87).
Springer DOI 9412
BibRef

Stockman, G.C., Kopstein, S., and Benett, S.,
Matching Images to Models for Registration and Object Detection via Clustering,
PAMI(4), No. 3, May 1982, pp. 229-241. (LNK) Try all pairs of image and model elements, generate rotation, scale and translation transformations between the two and cluster in this RST space. Clusters indicate many matches for these values this can then give the best global match. (Paper takes a long time to describe it-seems basically easy?) High level template matching? BibRef 8205

Stockman, G., Esteva, J.C.,
3D Object Pose from Clustering with Multiple Views,
PRL(3), 1985, pp. 279-286. BibRef 8500
Earlier:
Use of Geometrical Constraints and Clustering to Determine 3D Object Pose,
ICPR84(742-744). BibRef

Bani-Hashemi, A.,
A Fourier Approach to Camera Orientation,
PAMI(15), No. 11, November 1993, pp. 1197-1202.
IEEE DOI Fourier Descriptors. Analysis of regular patterns. BibRef 9311

Usoh, M., Buxton, H.,
SIMD Algorithm for Curved Object Recognition Using Grimson and Lozano-Perez Matching,
VC(10), 1993, pp. 160-172.
See also Localizing Overlapping Parts by Searching the Interpretation Tree. BibRef 9300

Hel-Or, Y., Werman, M.,
Pose Estimation by Fusing Noisy Data of Different Dimensions,
PAMI(17), No. 2, February 1995, pp. 195-201.
IEEE DOI BibRef 9502
And: Correction: PAMI(17), No. 5, May 1995, pp. 544. BibRef
Earlier:
Model Based Pose Estimation of Articulated and Constrained Objects,
ECCV94(A:262-273).
Springer DOI Constraint Satisfaction. BibRef

Hel-Or, Y., Werman, M.,
Constraint Fusion for Recognition and Localization of Articulated Objects,
IJCV(19), No. 1, July 1996, pp. 5-28.
Springer DOI 9608
BibRef
Earlier:
Constraint-Fusion for Localization and Interpretation of Constrained Objects,
CVPR94(39-45).
IEEE DOI BibRef

Brou, P.,
Using the Gaussian Image to Find the Orientation of Objects,
IJRR(3), No. 4, 1984, 89-125. BibRef 8400
And: MIT AI Memo-810, 1984. BibRef

Andresen, K., Hentrich, K., Huebner, B.,
Camera Orientation and 3D-Deformation Measurement by Use of Cross Gratings,
OptLas(22), No. 3, 1995, pp. 215-226. BibRef 9500

Olson, C.F.,
Probabilistic Indexing for Object Recognition,
PAMI(17), No. 5, May 1995, pp. 518-522.
IEEE DOI
PDF File. BibRef 9505
Earlier:
Fast Alignment Using Probabilistic Indexing,
CVPR93(387-392).
IEEE DOI BibRef
And:
Probabilistic Indexing: Recognizing 3D Objects from 2D Images Using the Probabilistic Peaking Effect,
UCBCSD-93-733, 1993. Indexing. Intended to be a fast version of indexing (as in Ben-Arie and Huttenlocher).
See also Connectionist Networks for Feature Indexing and Object Recognition.
See also Probabilistic Self-Localization for Mobile Robots. BibRef

Olson, C.F.,
Probabilistic Indexing: Recognizing 3D Objects from 2D Images Using Probabilistic Peaking Effect,
UCB/CDS93-733, UC Berkeley, May 1993, BibRef 9305

Olson, C.F.[Clark F.],
A Probabilistic Formulation for Hausdorff Matching,
CVPR98(150-156).
IEEE DOI Terrain Map from stereo. BibRef 9800

Olson, C.F.[Clark F.],
Fast Object Recognition By Selectively Examining Hypotheses,
UCBUC Berkeley, May 1994, BibRef 9405 Ph.D.Thesis (CS).
HTML Version.
PS File. BibRef

Olson, C.F.,
Efficient Pose Clustering Using A Randomized Algorithm,
IJCV(23), No. 2, June 1997, pp. 131-147.
DOI Link
HTML Version.
PDF File. 9708
BibRef
Earlier:
On the Speed and Accuracy of Object Recognition When Using Imperfect Grouping,
SCV95(449-454).
IEEE DOI BibRef
Earlier:
Time and Space Efficient Pose Clustering,
CVPR94(251-258).
IEEE DOI Cornell University. BibRef

Olson, C.F.[Clark F.],
Pose Sampling for Efficient Model-Based Recognition,
ISVC07(II: 781-790).
Springer DOI 0711
BibRef
And:
Pose clustering guided by short interpretation trees,
ICPR04(II: 149-152).
IEEE DOI 0409
BibRef

Huang, J.B., Chen, Z., Chia, T.L.,
Pose Determination of a Cylinder Using Reprojection Transformation,
PRL(17), No. 10, September 2 1996, pp. 1089-1099. BibRef 9609

Wells, III, W.M.,
Statistical Approaches to Feature-Based Object Recognition,
IJCV(21), No. 1-2, January 1997, pp. 63-98.
DOI Link 9704
BibRef

Wells, III, W.M.,
Statistical Object Recognition with the Expectation-Maximization Algorithm in Range-Derived Features,
DARPA93(839-850). BibRef 9300
And:
Posterior Marginal Pose Estimation,
DARPA92(745-751). BibRef
Earlier:
MAP Model Matching,
CVPR91(486-492).
IEEE DOI Match a detailed metrical object model using an alignment approach. BibRef

Baker, J.D.[Jonathan D.], Wells, III, W.M.[William M.],
Multiresolution Statistical Object Recognition,
ARPA94(II:1251-1256). BibRef 9400

Wells, III, W.M.[William M.],
Statistical Object Recognition,
MIT AI-TR-1398, January 1993. BibRef 9301 Ph.D.Thesis, MIT, 1992.
WWW Link. BibRef

Murino, V., Foresti, G.L.,
2D into 3D Hough-Space Mapping for Planar Object Pose Estimation,
IVC(15), No. 6, June 1997, pp. 435-444.
Elsevier DOI 9708
BibRef

Pece, A.E.C.[Arthur E.C.], Worrall, A.D.[Anthony D.],
A Statistically-Based Newton Method for Pose Refinement,
IVC(16), No. 8, June 1998, pp. 541-544.
Elsevier DOI 9807
BibRef

Ferryman, J.M., Worrall, A.D., Sullivan, G.D., Baker, K.D.,
A Generic Deformable Model for Vehicle Recognition,
BMVC95(xx-yy).
PDF File. 9509
BibRef

Worrall, A.D., Ferryman, J.M., Sullivan, G.D., Baker, K.D.,
Pose and Structure Recovery using Active Models,
BMVC95(xx-yy).
PDF File. 9509
BibRef

Worrall, A.D., Sullivan, G.D., Baker, K.D.,
Pose Refinement of Active Models Using Forces in 3D,
ECCV94(A:341-350).
Springer DOI BibRef 9400

Araújo, H.[Helder], Carceroni, R.L.[Rodrigo L.], Brown, C.M.[Christopher M.],
A Fully Projective Formulation to Improve the Accuracy of Lowe's Pose-Estimation Algorithm,
CVIU(70), No. 2, May 1998, pp. 227-238.
DOI Link BibRef 9805
Earlier:
A Full-Projective Improvement for Lowe's Pose-Estimation Algorithm,
DARPA97(875-880).
See also Robust Model-Based Motion Tracking Through the Integration of Search and Estimation. BibRef

Jacobs, D.W.[David W.], Basri, R.[Ronen],
3-D to 2-D Pose Determination with Regions,
IJCV(34), No. 2-3, August 1999, pp. 123-145.
DOI Link BibRef 9908
Earlier:
3D to 2D Recognition with Regions,
CVPR97(547-553).
IEEE DOI 9704
Part-based. pose estimation with region matches. BibRef

Basri, R.[Ronen], Jacobs, D.W.[David W.],
Projective Alignment with Regions,
PAMI(23), No. 5, May 2001, pp. 519-527.
IEEE DOI 0105
BibRef
Earlier: ICCV99(1158-1164).
IEEE DOI Use regions to determine the pose. Planar objects with transformations. When several regions are visible, pose can be recovered even with partial occlusions. BibRef

Montiel, E.[Eugenia], Aguado, A.S.[Alberto S.], Nixon, M.S.[Mark S.],
Improving the Hough Transform gathering process for affine transformations,
PRL(22), No. 9, July 2001, pp. 959-969.
Elsevier DOI 0106
BibRef

Aguado, A.S.[Alberto S.], Montiel, E.[Eugenia], Nixon, M.S.[Mark S.],
Invariant characterisation of the Hough transform for pose estimation of arbitrary shapes,
PR(35), No. 5, May 2002, pp. 1083-1097.
Elsevier DOI 0202
BibRef
Earlier: (spelled ization) BMVC00(xx-yy).
PDF File. 0009
BibRef

Jonsson, E.[Erik], Felsberg, M.[Michael],
Efficient computation of channel-coded feature maps through piecewise polynomials,
IVC(27), No. 11, 2 October 2009, pp. 1688-1694.
Elsevier DOI 0909
Channel-coded feature maps; Feature histograms; Soft histograms; Splines; Piecewise polynomials BibRef

Jonsson, E.[Erik], Felsberg, M.[Michael],
Accurate Interpolation in Appearance-Based Pose Estimation,
SCIA07(1-10).
Springer DOI 0706
BibRef
Earlier:
Correspondence-free Associative Learning,
ICPR06(II: 441-446).
IEEE DOI 0609
BibRef


Bao, S.Y.Z.[Sid Ying-Ze], Xiang, Y.[Yu], Savarese, S.[Silvio],
Object Co-detection,
ECCV12(I: 86-101).
Springer DOI 1210
objects in multiple views, which are the same, etc. BibRef

Bao, S.Y.Z.[Sid Ying-Ze], Savarese, S.[Silvio],
Semantic Structure from Motion: A Novel Framework for Joint Object Recognition and 3D Reconstruction,
WTFCV11(376-397).
Springer DOI 1210
BibRef

Ando, S., Kusachi, Y., Suzuki, A., Arakawa, K.,
Appearance Based Pose Estimation of 3D Object Using Support Vector Regression,
ICIP05(I: 341-344).
IEEE DOI 0512
BibRef

Bowden, R., Mitchell, T.A., Sarhadi, M.,
Reconstructing 3d Pose and Motion from a Single Camera View,
BMVC98(xx-yy). BibRef 9800

Shakunaga, T., Ohno, T.,
Successive Pose Clustering for Steroscopic Object Recognition,
MVA98(xx-yy). BibRef 9800

Meilhac, C.[Christophe], Nastar, C.[Chahab],
Robust fitting of 3D CAD models to video streams,
CIAP97(I: 661-668).
Springer DOI 9709
BibRef
And:
A Robust and Precise Approach for Model-Based 3D/2D Registration and Tracking,
SCIA97(xx-yy)
HTML Version. 9705
BibRef

Zerroug, M., Nevatia, R.,
Pose Estimation of Multi-Part Curved Objects,
SCV95(431-436).
IEEE DOI BibRef 9500 USC Computer Vision BibRef
And: ARPA96(831-836).
PDF File. U. of Southern California. Alignment of structured curved objects represented as generalized cylinders. BibRef

Chakravarthy, C.S., and Kasturi, R.,
Pose Clustering on Constraints for Object Recognition,
CVPR91(16-21).
IEEE DOI Basic, use segment features, match using Hough technique. BibRef 9100

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Grimson Object Recognition Papers .


Last update:Nov 26, 2024 at 16:40:19