12.2.4 Line Based Matching for Pose Estimation

Chapter Contents (Back)
Matching, Lines. Pose Estimation, Lines. Pose Estimation, Perspective.
See also 6D Object Pose Estimation.

Wu, Y.Y., Iyengar, S.S., Jain, R.C., and Bose, S.,
A New Generalized Computational Framework for Finding Object Orientation Using Perspective Trihedral Angle Constraint,
PAMI(16), No. 10, October 1994, pp. 961-975.
IEEE DOI BibRef 9410
Shape from Perspective Trihedral Angle Constraint,
IEEE DOI Similar technique to:
See also Perspective Angle Transform and Its Application to 3-D Configuration Recovery. BibRef

Dhome, M., Richetin, M., Lapreste, J.T., and Rives, G.,
Determination of the Attitude of 3-D Objects from a Single Perspective View,
PAMI(11), No. 12, December 1989, pp. 1265-1278.
IEEE DOI Three lines in the image correspond to three ridge lines of the object. This is used in a 8 degree equation to find the geometric transformation necessary to align the image and the model.
See also Inverse Perspective Transform Using Zero-Curvature Contour Points: Application to the Localization of Some Generalized Cylinders from a Single View. BibRef 8912

Dhome, M.[Michel], Yassine, A.[Ali], and Lavest, J.M.[Jean-Marc],
Determination of the Pose of an Articulated Object from a Single Perspective View,
PDF File. BibRef 9300

Phong, T.Q., Horaud, R., Yassine, A., Tao, P.D.,
Object Pose from 2-D to 3-D Point and Line Correspondences,
IJCV(15), No. 3, July 1995, pp. 225-243.
Springer DOI BibRef 9507

Phong, T.Q., Horaud, R., Yassine, A., and Pham, D.T.,
Optimal Estimation of Object Pose from a Single Perspective View,
IEEE DOI BibRef 9300

Dhome, M., Lapreste, J.T., Rives, G., and Richetin, M.,
Spatial Localization of Modelled Objects of Revolution in Monocular Perspective Vision,
Springer DOI BibRef 9000

Rives, G., Lapreste, J.T., Dhome, M., Richetin, M.,
Planar Partially Occluded Objects Scene Analysis,
ICPR86(1076-1079). BibRef 8600

Wong, A.K.C., Lu, S.W., and Rioux, M.,
Recognition and Shape Synthesis of 3D Objects Image Based on Attributed Hypergraphs,
PAMI(11), No. 3, March 1989, pp. 279-290.
IEEE DOI BibRef 8903
Earlier: A1, A2 Only:
Recognition and Knowledge Synthesis of 3-D Object Image Based on Attributed Hypergraph,
CVPR85(162-166). (Univ. of Waterloo) Laser range finder data. Generate and match a graph of the faces. BibRef

Sullivan, G.D.,
Visual Interpretation of Known Objects in Constrained Scenes,
Royal(B-337), 1992, pp. 361-370. BibRef 9200

Zhang, S., Sullivan, G.D., Baker, K.D.,
Relational Model Construction and 3D Object Recognition from Single 2D Monochromatic Image,
IVC(10), No. 5, June 1992, pp. 313-318.
Elsevier DOI BibRef 9206
Earlier: BMVC91(xx-yy).
PDF File. 9109

Zhang, S., Baker, K.D., and Sullivan, G.D.,
The Automatic Construction of a View-Independent Relational Model for 3-D Object Recognition,
PAMI(15), No. 6, June 1993, pp. 531-544.
IEEE DOI BibRef 9306
Earlier: A1, A3, A2:
Using Automatically Constructed View-Independent Relational Model in 3D Object Recognition,
Springer DOI Recognition by matching for pose. BibRef

Worrall, A.D., Baker, K.D., and Sullivan, G.D.,
Model Based Perspective Inversion,
IVC(7), No. 1, February 1989, pp. 17-23.
Elsevier DOI Model based recognition, similar to Lowe.
See also Three-Dimensional Object Recognition from Single Two-Dimensional Images. BibRef 8902

Worrall, A.D., Baker, K.D., Sullivan, G.D.,
Roll Angle Consistency Constraint,
IVC(8), No. 1, February 1990, pp. 78-84.
Elsevier DOI Reasoning on 3 orientation paramters. BibRef 9002

Das, S.[Subhodev], Bhanu, B.[Bir],
A System for Model-Based Object Recognition in Perspective Aerial Images,
PR(31), No. 4, April 1998, pp. 465-491.
Elsevier DOI 9803

Das, S., Bhanu, B.,
Computational Learning for Adaptive Computer Vision,
Springer2004. ISBN 0-387-23703-8.
HTML Version. BibRef 0400

Das, S., Bhanu, B.[Bir], Wu, X., and Braithwaite, R.N.[R. Neil],
A System for Aircraft Recognition in Perspective Aerial Images,
IEEE Abstract. BibRef 9400

Umeyama, S.[Shinji], Kasvand, T., and Hospital, M.,
Recognition and Positioning of Three-Dimensional Objects by Combining Matchings of Primitive Local Patterns,
CVGIP(44), No. 1, October 1988, pp. 58-76.
Elsevier DOI Recognize Three-Dimensional Objects. Model based recognition and pose estimation using edge information and surface information. BibRef 8810

Oka, R., Kasvand, T., and Rioux, M.,
Cross-Angle Transform for Viewer-Independent Recognition of 3-D Objects,
CVPR85(470-475). (National Research Council Canada) Recognize Three-Dimensional Objects. Descriptions based on the angles between pairs of faces, not directly the orientation of the faces. BibRef 8500

Jungert, E.[Erland],
Qualitative Spatial Reasoning from the Observers Point-of-View: Towards a Generalization of Symbolic Projection,
PR(27), No. 6, June 1994, pp. 801-813.
Elsevier DOI Spatial Reasoning. BibRef 9406

Chen, H.H.,
Pose Determination from Line-to-Plane Correspondences: Existence Condition and Closed-Form Solutions,
PAMI(13), No. 6, June 1991, pp. 530-541.
IEEE DOI BibRef 9106
Earlier: ICCV90(374-378).
IEEE DOI Lines correspond to the plane due to the use of planes of light. Closed form solutions are derived. BibRef

Penna, M.A.[Michael A.],
Determining Camera Parameters from the Perspective Projection of a Quadrilateral,
PR(24), No. 6, 1991, pp. 533-541.
Elsevier DOI Using a known quadrilateral, there is enough information to derive the camera position. BibRef 9100

Wong, K.C., Kittler, J.V.,
Recognizing polyhedral objects from a single perspective view,
IVC(11), No. 4, May 1993, pp. 211-220.
Elsevier DOI BibRef 9305
Earlier: BMVC92(590-599).
PDF File. 9209

Wong, K.C., Kittler, J.V., and Illingworth, J.,
Analysis of Straight Homogeneous Generalized Cylinders under Perspective Projection,
VF91(613-622). BibRef 9100

Wong, K.C.,
Pose Determination and Recognition of 3D Polyhedral Objects from a Single Perspective View,
CVPR93(late-paper). BibRef 9300

Christy, S.[Stèphane], Horaud, R.[Radu],
Iterative Pose Computation from Line Correspondences,
CVIU(73), No. 1, January 1999, pp. 137-144.
DOI Link BibRef 9901
Fast and reliable object pose estimation from line correspondences,
Springer DOI 9709

Pan, X.[Xiang], Lane, D.M.[David M.],
Pose determination from angles and relative line lengths using spherical trigonometry,
IVC(17), No. 13, 1 November 1999, pp. 937-953.
Elsevier DOI 9911

Gerwe, D.R.[David R.], Idell, P.S.[Paul S.],
Cramer-Rao Analysis of Orientation Estimation: Viewing Geometry Influences on the Information Conveyed by Target Features,
JOSA-A(20), No. 5, May 2003, pp. 797-816.
WWW Link.
PDF File. 0307

Gerwe, D.R.[David R.], Hill, J.L.[Jennifer L.], Idell, P.S.[Paul S.],
Cramer-Rao Analysis of Orientation Estimation: Influence of Target Model Uncertainties,
JOSA-A(20), No. 5, May 2003, pp. 817-826.
WWW Link. 0307

Liu, Y.H.[Yong-Huai], Holstein, H.[Horst],
Pseudo-linearizing collinearity constraint for accurate pose estimation from a single image,
PRL(25), No. 8, June 2004, pp. 955-965.
Elsevier DOI 0405
A pseudo linearization method for accurate pose estimation from a single image,
ICIP02(II: 557-560).

Paramanand, C., Rajagopalan, A.N.,
Image matching with higher-order geometric features,
JOSA-A(27), No. 4, April 2010, pp. 739-748.
WWW Link. 1003
Efficient geometric matching with higher-order features,
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 three-dimensional collinearity model,
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. BibRef

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.
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.
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,
Springer DOI 1304

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.
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.
TRPLP: Trifocal Relative Pose From Lines at Points,
Pose estimation, Geometry, Cameras, Pipelines, Pattern analysis, Tensors, Multiple view geometry, homotopy continuation, numerical algebraic geometry. Pipelines. BibRef

Goodwin, W.[Walter], Vaze, S.[Sagar], Havoutis, I.[Ioannis], Posner, I.[Ingmar],
Zero-Shot Category-Level Object Pose Estimation,
Springer DOI 2211

Rad, M.[Mahdi], Oberweger, M.[Markus], Lepetit, V.[Vincent],
Domain Transfer for 3D Pose Estimation from Color Images Without Manual Annotations,
Springer DOI 1906
Feature Mapping for Learning Fast and Accurate 3D Pose Inference from Synthetic Images,
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

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

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

Vakhitov, A.[Alexander], Colomina, L.F.[Luis Ferraz], Agudo, A.[Antonio], Moreno-Noguer, F.[Francesc],
Uncertainty-Aware Camera Pose Estimation from Points and Lines,
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

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

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,
contour primitives; object detection; pose estimation; shape primitives BibRef

Hirose, K.[Keisuke], Saito, H.[Hideo],
Fast Line Description for Line-based SLAM,
DOI Link 1301

Elqursh, A.[Ali], Elgammal, A.M.[Ahmed M.],
Line-based relative pose estimation,

Murray, D.W., Reid, I.D., Thompson, R.L.,
Real-time Visual Recovery of Pose using Line Tracking in Multiple Cameras,
HTML Version. BibRef 9800

Lanser, S., Lengauer, T.,
On the Selection of Candidates for Point and Line Correspondences,
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,
IEEE DOI BibRef 9400

Pathak, A., and Camps, O.I.,
Bayesian View Class Determination,
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).

Navab, N., and Faugeras, O.D.,
Monocular Pose Determination from Lines: Critical Sets and Maximum Number of Solutions,
IEEE DOI BibRef 9300

Shakunaga, T.,
Robust Line-Based Pose Estimation from a Single Image,
IEEE DOI BibRef 9300
Pose Estimation of Jointed Structures,

Ha, J., and Haralick, R.M.,
Estimation of the Position and Orientation of a Planar Surface Using Multiple Beams,
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,
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,
IEEE DOI BibRef 9200

Hong, K.S., Kim, K.N.,
Recognition Strategy Generation for Pose Estimation of Multiple 3-Dimensional Objects,
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,
IEEE DOI BibRef 9200

Stahs, T., Wahl, F.M.,
Object Recognition and Pose Estimation with a Fast and Versatile 3D Robot Sensor,
IEEE DOI BibRef 9200

Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Matching, Areas, Regions, Surfaces .

Last update:Jun 17, 2024 at 21:38:11