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Shape from Perspective Trihedral Angle Constraint,
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See also Perspective Angle Transform and Its Application to 3-D Configuration Recovery.
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9106
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ICCV90(374-378).
IEEE DOI Lines correspond to the plane due to the use of planes
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9305
Earlier:
BMVC92(590-599).
PDF File.
9209
BibRef
Wong, K.C.,
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Pose Determination and Recognition of 3D Polyhedral
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Iterative Pose Computation from Line Correspondences,
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Fast and reliable object pose estimation from line correspondences,
CAIP97(432-439).
Springer DOI
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BibRef
Pan, X.[Xiang],
Lane, D.M.[David M.],
Pose determination from angles and relative line lengths using
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Idell, P.S.[Paul S.],
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Hill, J.L.[Jennifer L.],
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Elsevier DOI
0405
BibRef
Earlier:
A pseudo linearization method for accurate pose estimation from a
single image,
ICIP02(II: 557-560).
IEEE DOI
0210
BibRef
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1003
BibRef
Earlier:
Efficient geometric matching with higher-order features,
ICPR08(1-4).
IEEE DOI
0812
lines and arcs.
BibRef
Fan, B.J.[Bao-Jie],
Du, Y.K.[Ying-Kui],
Cong, Y.[Yang],
Robust and accurate online pose estimation algorithm via efficient
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IET-CV(7), No. 5, October 2013, pp. 382-393.
DOI Link
1402
iterative methods
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Zhang, Y.Q.[Yue-Qiang],
Li, X.[Xin],
Liu, H.B.[Hai-Bo],
Shang, Y.[Yang],
Probabilistic approach for maximum likelihood estimation of pose
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IET-CV(10), No. 6, 2016, pp. 475-482.
DOI Link
1609
image segmentation. Pose from matched 3D model and 2D image lines.
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Zhang, Y.Q.[Yue-Qiang],
Li, X.[Xin],
Liu, H.B.[Hai-Bo],
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IEEE DOI
1706
Cameras, Image segmentation, Maximum likelihood estimation,
Noise measurement, Robustness,
Uncertainty, Maximum-likelihood approach, model-based tracking,
pose, estimation
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Xu, C.[Chi],
Zhang, L.[Lilian],
Cheng, L.[Li],
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Pose Estimation from Line Correspondences: A Complete Analysis and a
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IEEE DOI
1705
Cameras, Computational complexity, Iterative methods,
Mathematical model, Pose estimation,
Perspective-3-Line, camera pose estimation,
configuration analysis, perspective-n-line
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Zhang, L.[Lilian],
Xu, C.[Chi],
Lee, K.M.[Kok-Meng],
Koch, R.[Reinhard],
Robust and Efficient Pose Estimation from Line Correspondences,
ACCV12(III:217-230).
Springer DOI
1304
BibRef
Oñoro-Rubio, D.[Daniel],
López-Sastre, R.J.[Roberto J.],
Redondo-Cabrera, C.[Carolina],
Gil-Jiménez, P.[Pedro],
The challenge of simultaneous object detection and pose estimation:
A comparative study,
IVC(79), 2018, pp. 109-122.
Elsevier DOI
1811
Pose as regression or classification problem?
Pose estimation, Viewpoint estimation, Object detection,
Deep learning, Convolutional neural network
BibRef
Zhong, L.S.[Lei-Sheng],
Zhao, X.L.[Xiao-Lin],
Zhang, Y.[Yu],
Zhang, S.L.[Shun-Li],
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Occlusion-Aware Region-Based 3D Pose Tracking of Objects With
Temporally Consistent Polar-Based Local Partitioning,
IP(29), 2020, pp. 5065-5078.
IEEE DOI
2003
Image edge detection, Image color analysis,
Histograms, Solid modeling, occlusion detection
BibRef
Fabbri, R.,
Duff, T.,
Fan, H.,
Regan, M.H.,
da Costa de Pinho, D.,
Tsigaridas, E.,
Wampler, C.W.,
Hauenstein, J.D.,
Giblin, P.J.,
Kimia, B.,
Leykin, A.,
Pajdla, T.,
TRPLP: Trifocal Relative Pose From Lines at Points,
CVPR20(12070-12080)
IEEE DOI
2008
Pose estimation, Cameras, Pipelines, Geometry
BibRef
Rad, M.[Mahdi],
Oberweger, M.[Markus],
Lepetit, V.[Vincent],
Domain Transfer for 3D Pose Estimation from Color Images Without Manual
Annotations,
ACCV18(V:69-84).
Springer DOI
1906
BibRef
And:
Feature Mapping for Learning Fast and Accurate 3D Pose Inference from
Synthetic Images,
CVPR18(4663-4672)
IEEE DOI
1812
BibRef
Earlier: A2, A1, A3:
Making Deep Heatmaps Robust to Partial Occlusions for 3D Object Pose
Estimation,
ECCV18(XV: 125-141).
Springer DOI
1810
Training, Feature extraction,
Pose estimation, Color, Solid modeling
BibRef
Lee, K.[Kyoungoh],
Lee, I.[Inwoong],
Lee, S.H.[Sang-Hoon],
Propagating LSTM: 3D Pose Estimation Based on Joint Interdependency,
ECCV18(VII: 123-141).
Springer DOI
1810
BibRef
Li, C.[Chi],
Bai, J.[Jin],
Hager, G.D.[Gregory D.],
A Unified Framework for Multi-view Multi-class Object Pose Estimation,
ECCV18(XVI: 263-281).
Springer DOI
1810
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Miraldo, P.[Pedro],
Dias, T.[Tiago],
Ramalingam, S.[Srikumar],
A Minimal Closed-Form Solution for Multi-perspective Pose Estimation
using Points and Lines,
ECCV18(XVI: 490-507).
Springer DOI
1810
BibRef
Vakhitov, A.[Alexander],
Colomina, L.F.[Luis Ferraz],
Agudo, A.[Antonio],
Moreno-Noguer, F.[Francesc],
Uncertainty-Aware Camera Pose Estimation from Points and Lines,
CVPR21(4657-4666)
IEEE DOI
2111
Solid modeling, Uncertainty, Feature detection, Pose estimation,
Robot vision systems, Cameras, Robustness
BibRef
Vakhitov, A.[Alexander],
Funke, J.[Jan],
Moreno-Noguer, F.[Francesc],
Accurate and Linear Time Pose Estimation from Points and Lines,
ECCV16(VII: 583-599).
Springer DOI
1611
BibRef
Salaün, Y.[Yohann],
Marlet, R.[Renaud],
Monasse, P.[Pascal],
Robust and Accurate Line- and/or Point-Based Pose Estimation without
Manhattan Assumptions,
ECCV16(VII: 801-818).
Springer DOI
1611
BibRef
Berner, A.[Alexander],
Li, J.[Jun],
Holz, D.[Dirk],
Stuckler, J.[Jorg],
Behnke, S.[Sven],
Klein, R.[Reinhard],
Combining contour and shape primitives for object detection and pose
estimation of prefabricated parts,
ICIP13(3326-3330)
IEEE DOI
1402
contour primitives; object detection; pose estimation; shape primitives
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Hirose, K.[Keisuke],
Saito, H.[Hideo],
Fast Line Description for Line-based SLAM,
BMVC12(83).
DOI Link
1301
BibRef
Elqursh, A.[Ali],
Elgammal, A.M.[Ahmed M.],
Line-based relative pose estimation,
CVPR11(3049-3056).
IEEE DOI
1106
BibRef
Murray, D.W.,
Reid, I.D.,
Thompson, R.L.,
Real-time Visual Recovery of Pose using
Line Tracking in Multiple Cameras,
BMVC98(xx-yy).
HTML Version.
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9800
Lanser, S.,
Lengauer, T.,
On the Selection of Candidates for Point and Line Correspondences,
SCV95(157-162).
IEEE DOI Technische Universitat Munchen.
Use a priori knowledge to guide where to look, i.e. in a navigation
task you know how things should move.
BibRef
9500
Gandhi, T.,
Camps, O.I.,
Robust Feature Selection for Object Recognition using
Uncertain 2D Image Data,
CVPR94(281-287).
IEEE DOI
BibRef
9400
Pathak, A., and
Camps, O.I.,
Bayesian View Class Determination,
CVPR93(407-412).
IEEE DOI Match features to a model for recognition of the pose.
BibRef
9300
Lu, H.Y.[Hai-Yuan],
Shapiro, L.G.[Linda G.], and
Camps, O.I.[Octavia I.],
A Relational Pyramid Approach to View Class Determination,
3DWS89(177-183).
BibRef
8900
Shapiro, L.G.[Linda G.], and
Lu, H.Y.[Hai-Yuan],
The Use of a Relational Pyramid Representation for View Classes
in a CAD-to-Vision System,
ICPR88(I: 379-381).
IEEE DOI
8811
BibRef
Navab, N., and
Faugeras, O.D.,
Monocular Pose Determination
from Lines: Critical Sets and Maximum Number of Solutions,
CVPR93(254-260).
IEEE DOI
BibRef
9300
Shakunaga, T.,
Robust Line-Based Pose Estimation from a Single Image,
ICCV93(545-550).
IEEE DOI
BibRef
9300
Earlier:
Pose Estimation of Jointed Structures,
CVPR91(566-572).
IEEE DOI
BibRef
Ha, J., and
Haralick, R.M.,
Estimation of the Position and
Orientation of a Planar Surface Using Multiple Beams,
CVPR93(628-629).
IEEE DOI
BibRef
9300
Chen, J.L.,
Stockman, G.C., and
Rao, K.G.,
Recovering and Tracking Pose of Curved 3D Objects from 2D Images,
CVPR93(233-239).
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9300
You, Y.C.,
Lee, J.D.,
Lee, J.Y.,
Chen, C.H.,
Determining Location and Orientation of a Labelled Cylinder
Using Point-Pair Estimation Algorithm,
ICPR92(I:354-357).
IEEE DOI
BibRef
9200
Hong, K.S.,
Kim, K.N.,
Recognition Strategy Generation for Pose Estimation of Multiple
3-Dimensional Objects,
ICPR92(I:612-615).
IEEE DOI
BibRef
9200
Safaee-Rad, R.,
Tchoukanov, I.,
Benhabib, B.,
Smith, K.C.,
3D-Pose Estimation From A Quadratic Curved Feature In
Two Perspective Views,
ICPR92(I:341-344).
IEEE DOI
BibRef
9200
Stahs, T.,
Wahl, F.M.,
Object Recognition and Pose Estimation with a Fast and
Versatile 3D Robot Sensor,
ICPR92(I:684-687).
IEEE DOI
BibRef
9200
Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Matching, Areas, Regions, Surfaces .