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A New Generalized Computational Framework for Finding Object
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9410
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Shape from Perspective Trihedral Angle Constraint,
CVPR93(261-266).
IEEE DOI Similar technique to:
See also Perspective Angle Transform and Its Application to 3-D Configuration Recovery.
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See also Inverse Perspective Transform Using Zero-Curvature Contour Points: Application to the Localization of Some Generalized Cylinders from a Single View.
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Recognition and Knowledge Synthesis of 3-D Object Image
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PDF File.
9109
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9306
Earlier: A1, A3, A2:
Using Automatically Constructed View-Independent Relational Model
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Springer DOI Recognition by matching for pose.
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See also Three-Dimensional Object Recognition from Single Two-Dimensional Images.
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Cross-Angle Transform for Viewer-Independent
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Pose Determination from Line-to-Plane
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IEEE DOI
BibRef
9106
Earlier:
ICCV90(374-378).
IEEE DOI Lines correspond to the plane due to the use of planes
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BibRef
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Determining Camera Parameters from the Perspective
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9100
Wong, K.C.,
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9305
Earlier:
BMVC92(590-599).
PDF File.
9209
BibRef
Wong, K.C.,
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Analysis of Straight Homogeneous Generalized Cylinders under
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Wong, K.C.,
Pose Determination and Recognition of 3D Polyhedral
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Christy, S.[Stèphane],
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Iterative Pose Computation from Line Correspondences,
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9901
Earlier:
Fast and reliable object pose estimation from line correspondences,
CAIP97(432-439).
Springer DOI
9709
BibRef
Pan, X.[Xiang],
Lane, D.M.[David M.],
Pose determination from angles and relative line lengths using
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9911
BibRef
Gerwe, D.R.[David R.],
Idell, P.S.[Paul S.],
Cramer-Rao Analysis of Orientation Estimation: Viewing Geometry
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0307
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Hill, J.L.[Jennifer L.],
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0307
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Liu, Y.H.[Yong-Huai],
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Pseudo-linearizing collinearity constraint for accurate pose estimation
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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
Paramanand, C.,
Rajagopalan, A.N.,
Image matching with higher-order geometric features,
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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
BibRef
Zhang, Y.Q.[Yue-Qiang],
Li, X.[Xin],
Liu, H.B.[Hai-Bo],
Shang, Y.[Yang],
Probabilistic approach for maximum likelihood estimation of pose
using lines,
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],
Shang, Y.[Yang],
Comparative Study of Visual Tracking Method:
A Probabilistic Approach for Pose Estimation Using Lines,
CirSysVideo(27), No. 6, June 2017, pp. 1222-1234.
IEEE DOI
1706
Cameras, Image segmentation, Maximum likelihood estimation,
Noise measurement, Robustness,
Uncertainty, Maximum-likelihood approach, model-based tracking,
pose, estimation
BibRef
Xu, C.[Chi],
Zhang, L.[Lilian],
Cheng, L.[Li],
Koch, R.[Reinhard],
Pose Estimation from Line Correspondences: A Complete Analysis and a
Series of Solutions,
PAMI(39), No. 6, June 2017, pp. 1209-1222.
IEEE DOI
1705
Cameras, Computational complexity, Iterative methods,
Mathematical model, Pose estimation,
Perspective-3-Line, camera pose estimation,
configuration analysis, perspective-n-line
BibRef
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],
Zhang, L.[Li],
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.[Ricardo],
Duff, T.[Timothy],
Fan, H.Y.[Hong-Yi],
Regan, M.H.[Margaret H.],
da Costa-de Pinho, D.[David],
Tsigaridas, E.[Elias],
Wampler, C.W.[Charles W.],
Hauenstein, J.D.[Jonathan D.],
Giblin, P.J.[Peter J.],
Kimia, B.B.[Benjamin B.],
Leykin, A.[Anton],
Pajdla, T.[Tomas],
Trifocal Relative Pose From Lines at Points,
PAMI(45), No. 6, June 2023, pp. 7870-7884.
IEEE DOI
2305
BibRef
Earlier:
TRPLP: Trifocal Relative Pose From Lines at Points,
CVPR20(12070-12080)
IEEE DOI
2008
Pose estimation, Geometry, Cameras, Pipelines, Pattern analysis,
Tensors, Multiple view geometry, homotopy continuation,
numerical algebraic geometry.
Pipelines.
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
BibRef
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
BibRef
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.
BibRef
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).
IEEE DOI Tracking with examples that look a lot like 2-D images.
BibRef
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 .