Birk, J.R.,
A Computation for Robots to Orient and Position Hand Held Workpieces,
SMC(6), No. 10, October 1976, pp. 665-671.
BibRef
7610
Kelley, R.B.[Robert B.],
Birk, J.R.[John R.],
Chen, N.Y.[Nai-Yung],
Estimating Workpiece Pose Using the Feature Points Method,
US_Patent4,402,053, Aug 30, 1983
WWW Link.
BibRef
8308
And: A3, A2, A1:
DraftManuscript dated Nov 1, 1978 and a revision.
BibRef
And: A2, A1, A3:
Visually Estimating Workpiece Pose in a Robot Hand
Using the Feature Points Method,
Draft
Camera Calibration.
Point Matching. No notes on publishing.
Match extracted points with feature points (corners and small holes)
in the model.
Technique involves rotating the object in the robot hand after locating it.
BibRef
Birk, J.R., and
Kelley, R.B.,
Chen, N.Y.,
Wilson, L.,
Image Feature Extraction Using Diameter Limited Gradient Direction
Histograms,
PAMI(1), No. 2, April 1979, pp. 228-235.
BibRef
7904
Earlier:
PRAI-78(xx).
(Wrong page numbers.)
Extract objects using histograms of edge directions. Find the pose of the
objects.
BibRef
Tella, R.,
Birk, J.R., and
Kelley, R.B.,
General Purpose Hands for Bin-Picking Robots,
SMC(12), 1982, pp. 828-837.
BibRef
8200
Dessimoz, J.D.,
Birk, J.R.,
Kelley, R.B.,
Martins, H.A.S., and
I, C.L.[Chi Lin],
Matched Filters for Bin Picking,
PAMI(6), No. 6, November 1984, pp. 686-697.
BibRef
8411
Kelley, R.B.,
Birk, J.R.,
Martins, H.A.S.,
Tella, R.,
A Robot System Which Acquires Cylindrical Workpieces from Bins,
SMC(12), 1982, pp. 204-213.
BibRef
8200
Kelley, R.B.,
Martins, H.A.S.,
Birk, J.R.,
Dessimoz, J.D.,
Three Vision Algorithms for Acquiring Workpieces from Bins,
PIEEE(71), 1983, pp. 803-820.
BibRef
8300
Birk, J.R., and
Kelley, R.B.,
Badami, V.V.,
Workpiece Orientation Correction with a Robot Arm
Using Visual Information,
IJCAI77(758).
BibRef
7700
Augusteijn, M.F.[Marijke F.],
Dyer, C.R.[Charles R.],
Recognition and Recovery of the Three-Dimensional Orientation
of Planar Point Patterns,
CVGIP(36), No. 1, October 1986, pp. 76-99.
Elsevier DOI
BibRef
8610
Earlier:
Model-based Shape from Contour and Point Patterns,
CVPR85(100-105).
(Univ. of Colorado at Colorado Springs and Univ. of Wisconsin)
Recognition, Using Shape. Given a known pattern or shape, compute the surface orientation
using an iterative method and no prior correspondence.
BibRef
Horn, B.K.P.,
Closed Form Solutions of Absolute Orientation Using
Orthonormal Matrices,
JOSA-A(5), No. 7, 1987, pp. 1127-1135.
See also Relative Orientation.
BibRef
8700
Horn, B.K.P.,
Closed Form Solutions of Absolute Orientation Using Unit Quaternions,
JOSA-A(4), No. 4, April 1987, pp. 629-642.
BibRef
8704
Linnainmaa, S.[Seppo],
Harwood, D.A.[David],
Davis, L.S.,
Pose Determination of a Three-Dimensional Object Using Triangle Pairs,
PAMI(10), No. 5, September 1988, pp. 634-647.
IEEE DOI
BibRef
8809
Earlier:
Triangle-Based Pose Determination of 3-D Objects,
ICPR86(116-118).
Hough. Pose estimation of a three dimensional object, by a Hough approach using all
6 parameters of the position. Uses triples of points on the object
matched to triples of points on the image. Initial experiments on
simple objects.
BibRef
Pehkonen, K.,
Harwood, D.,
Davis, L.S.,
Parallel Calculation of 3-D Pose of a Known Object in a Single View,
PRL(12), 1991, pp. 353-361.
BibRef
9100
Walker, M.W.[Michael W.],
Shao, L.J.[Le-Jun],
Volz, R.A.[Richard A.],
Estimating 3-D Location Parameters Using Dual Number Quaternions,
CVGIP(54), No. 3, November 1991, pp. 358-367.
Elsevier DOI
BibRef
9111
Haralick, R.M.,
Joo, H.,
Lee, C.N.,
Zhuang, X.,
Vaidya, V.G., and
Kim, M.B.,
Pose Estimation from Corresponding Point Data,
SMC(19), No. 6, November/December 1989, pp. 1426-1446.
BibRef
8911
Earlier: A1, A3, A4, A5, A6 Only:
CVWS87(258-263).
Pose Estimation, Evaluation. Closed form solutions for 2-D to 2-D and 3-D to 3-D pose
estimations. For perspective 2-D to 3-D, a convergent iterative
solution is given, for 2-D perspective to 2-D perspective, a linear
solution is given. This is also an argument for error analysis and
error propagation analysis.
BibRef
Haralick, R.M.,
Joo, H.,
2D-3D Pose Estimation,
ICPR88(I: 385-391).
IEEE DOI
BibRef
8800
Umeyama, S.,
Least-Squares Estimation of Transformation
Parameters Between Two Point Patterns,
PAMI(13), No. 4, April 1991, pp. 376-380.
IEEE DOI Follows from Arun and Horn work.
Parameterized transformations following from:
See also Eigen Decomposition Approach to Weighted Graph Matching Problems, An.
BibRef
9104
Umeyama, S.,
Parameterized Point Pattern Matching and Its
Application to Recognition of Object Families,
PAMI(15), No. 2, February 1993, pp. 136-144.
IEEE DOI The point positions may be parameterized to allow
for some articulation of the parts.
See also Eigen Decomposition Approach to Weighted Graph Matching Problems, An.
BibRef
9302
Yang, M.C.K.,
Lee, J.S.,
Object Identification From Multiple Images Based on
Point Matching Under A General Transformation,
PAMI(16), No. 7, July 1994, pp. 751-756.
IEEE DOI
SAR Imagery. Points are 3-D locations from SAR data.
BibRef
9407
Gee, A.[Andrew],
Cipolla, R.[Roberto],
Determining the Gaze of Faces in Images,
IVC(12), No. 10, December 1994, pp. 639-647.
Elsevier DOI
Application, Faces.
Bayes Nets.
PS File.
BibRef
9412
And:
Estimating Gaze from a Single View of a Face,
ICPR94(A:758-760).
IEEE DOI Track features to estimate the pose of the face.
BibRef
Gee, A.[Andrew],
Cipolla, R.[Roberto],
Fast Visual Tracking by Temporal Consensus,
IVC(14), No. 2, March 1996, pp. 105-114.
Elsevier DOI
9607
BibRef
Earlier:
Cambridge UniversityTechnical Report CUED/F-INFENG/TR 207.
PS File.
BibRef
Arun, K.S.,
Huang, T.S., and
Blostein, S.D.,
Least-Squares Fitting of Two 3-D Point Sets,
PAMI(9), No. 5, September 1987, pp. 698-700.
This is not strictly motion, but is deriving R
and T when given a pair of matching 3-D points.
BibRef
8709
DeMenthon, D.F., and
Davis, L.S.,
Exact and Approximate Solutions of the
Perspective-Three-Point Problem,
PAMI(14), No. 11, November 1992, pp. 1100-1105.
IEEE DOI Match image and model triangles to get pose.
BibRef
9211
Oberkampf, D.,
DeMenthon, D.F., and
Davis, L.S.,
Iterative Pose Estimation Using Coplanar Feature Points,
CVIU(63), No. 3, May 1996, pp. 495-511.
DOI Link
9606
BibRef
Earlier:
Iterative Pose Estimation Using Coplanar Points,
CVPR93(626-627).
IEEE DOI POSIT
BibRef
DeMenthon, D.F.[Daniel F.],
Computer vision system for position monitoring in three dimensions
using non-coplanar light sources attached to a monitored object,
US_Patent5,227,985, Jul 13, 1993
WWW Link.
BibRef
9307
DeMenthon, D.F., and
Davis, L.S.,
Model-Based Object Pose in 25 Lines of Code,
IJCV(15), No. 1-2, June 1995, pp. 123-141.
Springer DOI
BibRef
9506
Earlier:
ECCV92(335-343).
Springer DOI
BibRef
And:
DARPA92(753-761).
Of course it is Mathematica code.
BibRef
Krishnan, R.[Radha],
Sommer, III, H.J.,
Spidaliere, P.D.[Peter D.],
Monocular Pose of a Rigid Body Using Point Landmarks,
CVGIP(55), No. 3, May 1992, pp. 307-316.
Elsevier DOI Analysis of the problem and how it is done.
BibRef
9205
Chen, S.W.[Sei-Wang],
Jain, A.K.[Anil K.],
Strategies of Multi-View and Multi-Matching for 3D Object Recognition,
CVGIP(57), No. 1, January 1993, pp. 121-130.
DOI Link
BibRef
9301
Chen, S.W.[Sei-Wang],
Stockman, G.C.[George C.], and
Shrikhande, N.[Neelima],
Computing a Pose Hypothesis from a Small Set of 3-D Object Features,
MSU-ENGR-87-001, Department of Computer Science,
Michigan State University, 1987.
BibRef
8700
Haralick, R.M.,
Lee, C.N.[Chung-Nan],
Ottenberg, K.[Karsten],
Nölle, M.[Michael],
Review and Analysis of Solutions of the Three Point
Perspective Pose Estimation Problem,
IJCV(13), No. 3, December 1994, pp. 331-356.
Springer DOI
BibRef
9412
Earlier:
Analysis and Solutions of the Three Point Perspective Pose
Estimation Problem,
CVPR91(592-598).
IEEE DOI
BibRef
Wlczek, P.,
Maccato, A.,
de Figueiredo, R.J.P.,
Pose Estimation Of 3-Dimensional Objects From Single Camera Images,
DSP(5), No. 3, July 1995, pp. 176-183.
BibRef
9507
Wirtz, B., and
Maggioni, C.,
3-D Pose Estimation by an Improved Kohonen-Net,
VF91(593-602).
A Neural-net apporach for self-organizing feature maps.
BibRef
9100
Alter, T.D.,
3-D Pose From 3 Points Using Weak-Perspective,
PAMI(16), No. 8, August 1994, pp. 802-808.
IEEE DOI
BibRef
9408
Earlier:
3D Pose from Three Corresponding Points Under
Weak-Perspective Projection,
MIT AI Memo-1378, July 1992.
WWW Link. One feasible solution plus reflection.
BibRef
Huang, T.S.[Thomas S.],
Bruckstein, A.M.[Alfred M.],
Holt, R.J.[Robert J.],
Netravali, A.N.[Arun N.],
Uniqueness of 3D Pose under Weak Perspective: A Geometrical Proof,
PAMI(17), No. 12, December 1995, pp. 1220-1221.
IEEE DOI Geometric proof of the one feasible solution plus reflection conclusion
of
See also 3-D Pose From 3 Points Using Weak-Perspective. and
See also Recognizing Solid Objects by Alignment with an Image.
BibRef
9512
Bruckstein, A.M.[Alfred M.],
Holt, R.J.[Robert J.],
Huang, T.S.[Thomas S.],
Netravali, A.N.[Arun N.],
Optimum Fiducials Under Weak Perspective Projection,
IJCV(35), No. 3, December 1999, pp. 223-244.
DOI Link
BibRef
9912
Earlier:
ICCV99(67-72).
IEEE DOI
BibRef
Bruckstein, A.M.[Alfred M.],
Holt, R.J.[Robert J.],
Netravali, A.N.[Arun N.],
Iterative algorithm for optimal fiducials under weak perspective
projection,
IJIST(19), No. 1, March 2009, pp. 27-36.
DOI Link
0902
BibRef
Horaud, R.[Radu],
Dornaika, F.[Fadi],
Lamiroy, B.[Bart],
Christy, S.[Stephane],
Object Pose:
The Link Between Weak Perspective, Paraperspective, and Full Perspective,
IJCV(22), No. 2, March 1997, pp. 173-189.
DOI Link
9706
BibRef
Earlier: A1, A4, A2 only:
TRINRIA, September 1994.
BibRef
Horaud, R.[Radu],
Christy, S.[Stephane],
Dornaika, F.[Fadi],
Lamiroy, B.[Bart],
Object Pose: Links Between Paraperspective and Perspective,
ICCV95(426-433).
IEEE DOI
BibRef
9500
Dornaika, F.[Fadi],
Garcia, C.[Christophe],
Pose Estimation using Point and Line Correspondences,
RealTimeImg(5), No. 3, June 1999, pp. 215-230.
BibRef
9906
Earlier:
Object pose by affine iterations,
CIAP97(I: 478-485).
Springer DOI
9709
BibRef
Golda, S.[Steven],
Rangarajana, A.[Anand],
Lua, C.P.[Chien-Ping],
Pappua, S.[Suguna],
Mjolsnessa, E.[Eric],
New Algorithms for 2D and 3D Point Matching:
Pose Estimation and Correspondence,
PR(31), No. 8, August 1998, pp. 1019-1031.
Elsevier DOI
9807
SoftAssign
BibRef
Liu, Y.H.[Yong-Huai],
Rodrigues, M.A.[Marcos A.],
Statistical image analysis for pose estimation without point
correspondences,
PRL(22), No. 11, September 2001, pp. 1191-1206.
Elsevier DOI
0108
BibRef
Earlier:
Correspondenceless Motion Estimation from Range Images,
ICCV99(654-659).
IEEE DOI
BibRef
And:
Using Rigid Constraints to Analyse Motion Parameters from Two Sets of
3D Corresponding Point Pattern,
CAIP99(321-328).
Springer DOI
9909
BibRef
Rodrigues, M.A.[Marcos A.],
Liu, Y.H.[Yong-Huai],
Distance Constraint Based Iterative Structure and Pose Estimation from
a Single Image,
ICIP00(Vol I: 501-504).
IEEE DOI
0008
BibRef
Earlier:
Motion Parameter Constraints Analysis From a Single Image,
ICIP99(III:704-708).
IEEE DOI
BibRef
David, P.[Philip],
DeMenthon, D.F.[Daniel F.],
Duraiswami, R.[Ramani],
Samet, H.[Hanan],
SoftPOSIT: Simultaneous Pose and Correspondence Determination,
IJCV(59), No. 3, September-October 2004, pp. 259-284.
DOI Link
0405
BibRef
Earlier:
ECCV02(III: 698 ff.).
Springer DOI
0205
BibRef
And:
Simultaneous pose and correspondence determination using line features,
CVPR03(II: 424-431).
IEEE DOI
0307
Combine Gold SoftAssign(
See also New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence. )
and DeMenthon POSIT (
See also Iterative Pose Estimation Using Coplanar Feature Points. ).
BibRef
David, P.[Philip],
DeMenthon, D.F.[Daniel F.],
Duraiswami, R.[Ramani],
Samet, H.[Hanan],
Evaluation of the Softposit Model-to-image Registration Algorithm,
UMD-- TR4340, July 2002.
WWW Link.
BibRef
0207
Kanatani, K.[Kenichi],
Kanazawa, Y.S.[Yasu-Shi],
Automatic Thresholding For Correspondence Detection,
IJIG(4), No. 1, January 2004, pp. 21-33.
0401
BibRef
Lin, L.H.[Li-Heng],
Lawrence, P.D.[Peter D.],
Hall, R.[Robert],
Robust outdoor stereo vision SLAM for heavy machine rotation sensing,
MVA(24), No. 1, January 2013, pp. 205-226.
WWW Link.
1301
Camera pose using sun angle and shadows. Measure mining rope rotation about
vertical axix.
BibRef
Collins, T.[Toby],
Bartoli, A.E.[Adrien E.],
Infinitesimal Plane-Based Pose Estimation,
IJCV(109), No. 3, September 2014, pp. 252-286.
Springer DOI
1408
Pose of a plane given set of corresponding points.
BibRef
Zhou, H.Y.[Hao-Yin],
Zhang, T.[Tao],
Lu, W.N.[Wei-Ning],
Vision-Based Pose Estimation From Points With Unknown Correspondences,
IP(23), No. 8, August 2014, pp. 3468-3477.
IEEE DOI
1408
computer vision
BibRef
Bratanic, B.[Bla],
Pernu, F.[Franjo],
Likar, B.[Botjan],
Tomaevic, D.[Dejan],
Real-time pose estimation of rigid objects in heavily cluttered
environments,
CVIU(141), No. 1, 2015, pp. 38-51.
Elsevier DOI
1512
object pose estimation
BibRef
Hossein-Nejad, Z.[Zahra],
Nasri, M.[Mehdi],
RKEM: Redundant Keypoint Elimination Method in Image Registration,
IET-IPR(11), No. 5, April 2017, pp. 273-284.
DOI Link
1706
BibRef
Wu, P.C.[Po-Chen],
Tseng, H.Y.[Hung-Yu],
Yang, M.H.[Ming-Hsuan],
Chien, S.Y.[Shao-Yi],
Direct pose estimation for planar objects,
CVIU(172), 2018, pp. 50-66.
Elsevier DOI
1812
BibRef
Earlier: A2, A1, A3, A4:
Direct 3D pose estimation of a planar target,
WACV16(1-9)
IEEE DOI
1606
Pose estimation, Pose tracking, Augmented reality.
Cameras. 3D pose from 2D.
First a template match, then refinement.
BibRef
Bazargani, H.[Hamid],
Bilaniuk, O.[Olexa],
Laganičre, R.[Robert],
A fast and robust homography scheme for real-time planar target
detection,
RealTimeIP(15), No. 4, December 2018, pp. 739-758.
Springer DOI
1812
Pose for planar targets.
BibRef
Liu, H.S.[Hong-Sen],
Cong, Y.[Yang],
Yang, C.G.[Chen-Guang],
Tang, Y.D.[Yan-Dong],
Efficient 3D object recognition via geometric information
preservation,
PR(92), 2019, pp. 135-145.
Elsevier DOI
1905
Stacked 3D feature encoder, 3D object recognition,
6-DOF pose estimation, Geometric information preservation
BibRef
Liu, H.S.[Hong-Sen],
Cong, Y.[Yang],
Sun, G.[Gan],
Tang, Y.D.[Yan-Dong],
Robust 3-D Object Recognition via View-Specific Constraint,
SMCS(51), No. 11, November 2021, pp. 7109-7119.
IEEE DOI
2110
Feature extraction, Object recognition, Databases, Annotations,
Surface texture, Robots, Surface treatment, voting strategy
BibRef
Liu, Y.P.[Yuan-Peng],
Zhou, L.S.[Lai-Shui],
Zong, H.[Hua],
Gong, X.X.[Xiao-Xi],
Wu, Q.Y.[Qiao-Yun],
Liang, Q.X.[Qing-Xiao],
Wang, J.[Jun],
Regression-Based Three-Dimensional Pose Estimation for Texture-Less
Objects,
MultMed(21), No. 11, November 2019, pp. 2776-2789.
IEEE DOI
1911
CNN to get features, regression to match.
Pose estimation, Feature extraction,
Training, Image edge detection, Correlation, Cost function,
pose regression
BibRef
Cui, Z.C.[Zhi-Chao],
Chen, Z.[Zeqi],
Zhang, C.[Chi],
Meng, G.F.[Gao-Feng],
Liu, Y.H.[Yue-Hu],
Zhao, X.[Xiangmo],
DDGPnP: Differential degree graph based PnP solution to handle
outliers,
CVIU(248), 2024, pp. 104130.
Elsevier DOI
2409
Outlier removal, Perspective-n-point, Pose estimation,
Differential degree graph, Maximum clique
BibRef
Cheng, W.T.[Wen-Tao],
Luo, M.[Minxing],
MVP: One-Shot Object Pose Estimation by Matching With Visible Points,
SPLetters(31), 2024, pp. 2760-2764.
IEEE DOI
2410
Point cloud compression, Feature extraction, Pose estimation,
Image reconstruction, Solid modeling, Vectors, Transformers, Indexes,
feature matching
BibRef
Nguyen, V.N.[Van Nguyen],
Groueix, T.[Thibault],
Salzmann, M.[Mathieu],
Lepetit, V.[Vincent],
GigaPose: Fast and Robust Novel Object Pose Estimation via One
Correspondence,
CVPR24(9903-9913)
IEEE DOI Code:
WWW Link.
2410
Solid modeling, Accuracy, Source coding, Impedance matching,
Pose estimation, Predictive models, object pose estimation
BibRef
Chen, Y.[Yamei],
Di, Y.[Yan],
Zhai, G.Y.[Guang-Yao],
Manhardt, F.[Fabian],
Zhang, C.Y.G.[Chen-Yang-Guang],
Zhang, R.[Ruida],
Tombari, F.[Federico],
Navab, N.[Nassir],
Busam, B.[Benjamin],
SecondPose: SE(3)-Consistent Dual-Stream Feature Fusion for
Category-Level Pose Estimation,
CVPR24(9959-9969)
IEEE DOI
2410
Shape, Pose estimation, Semantics, Feature extraction, Cameras
BibRef
Nguyen, V.N.[Van Nguyen],
Groueix, T.[Thibault],
Ponimatkin, G.[Georgy],
Hu, Y.L.[Yin-Lin],
Marlet, R.[Renaud],
Salzmann, M.[Mathieu],
Lepetit, V.[Vincent],
NOPE: Novel Object Pose Estimation from a Single Image,
CVPR24(17923-17932)
IEEE DOI
2410
Training, Solid modeling, Visualization, Accuracy,
Computational modeling, Pose estimation, object pose estimation
BibRef
Zheng, L.F.[Lin-Fang],
Tse, T.H.E.[Tze Ho Elden],
Wang, C.[Chen],
Sun, Y.[Yinghan],
Chen, H.[Hua],
Leonardis, A.[Ales],
Zhang, W.[Wei],
Chang, H.J.[Hyung Jin],
GeoReF: Geometric Alignment Across Shape Variation for Category-level
Object Pose Refinement,
CVPR24(10693-10703)
IEEE DOI Code:
WWW Link.
2410
Point cloud compression, Shape, Soft sensors, Pose estimation,
Computer architecture, Predictive models
BibRef
Ventura, J.[Jonathan],
Kukelova, Z.[Zuzana],
Sattler, T.[Torsten],
Baráth, D.[Dániel],
Absolute Pose from One or Two Scaled and Oriented Features,
CVPR24(20870-20880)
IEEE DOI Code:
WWW Link.
2410
Location awareness, Accuracy, Simultaneous localization and mapping,
Measurement units, image-based localization
BibRef
Tirado-Garín, J.[Javier],
Civera, J.[Javier],
From Correspondences to Pose: Non-Minimal Certifiably Optimal
Relative Pose Without Disambiguation,
CVPR24(403-412)
IEEE DOI Code:
WWW Link.
2410
Geometry, Codes, Accuracy, Pose estimation, Buildings, relative pose,
non-minimal solver, semidefinite programming, epipolar geometry
BibRef
Edstedt, J.[Johan],
Bökman, G.[Georg],
Zhao, Z.J.[Zhen-Jun],
DeDoDe v2: Analyzing and Improving the DeDoDe Keypoint Detector,
IMW24(4245-4253)
IEEE DOI
2410
Training, Schedules, Codes, Pose estimation, Detectors, image matching,
keypoint detection, structure-from-motion, two-view geometry,
local feature matching
BibRef
Nguyen, K.D.[Khoi Duc],
Li, C.[Chen],
Lee, G.H.[Gim Hee],
ESCAPE: Encoding Super-keypoints for Category-Agnostic Pose
Estimation,
CVPR24(23491-23500)
IEEE DOI Code:
WWW Link.
2410
Sensitivity, Computer network reliability,
Computational modeling, Pose estimation, Encoding, Bayes methods,
2d pose estimation
BibRef
Zhao, C.[Chen],
Hu, Y.L.[Yin-Lin],
Salzmann, M.[Mathieu],
LocPoseNet: Robust Location Prior for Unseen Object Pose Estimation,
3DV24(1072-1081)
IEEE DOI Code:
HTML Version.
2408
Location awareness, Correlation, Pose estimation, Noise, Pipelines, Robustness
BibRef
Lin, C.[Chen],
Hanson, A.J.[Andrew J.],
Hanson, S.M.[Sonya M.],
Algebraically rigorous quaternion framework for the neural network
pose estimation problem,
ICCV23(14051-14060)
IEEE DOI
2401
BibRef
Legrand, A.[Antoine],
Detry, R.[Renaud],
de Vleeschouwer, C.[Christophe],
End-to-end Neural Estimation of Spacecraft Pose with Intermediate
Detection of Keypoints,
AI4Space22(154-169).
Springer DOI
2304
BibRef
Ventura, J.[Jonathan],
Kukelova, Z.[Zuzana],
Sattler, T.[Torsten],
Baráth, D.[Dániel],
P1AC: Revisiting Absolute Pose From a Single Affine Correspondence,
ICCV23(19694-19704)
IEEE DOI Code:
WWW Link.
2401
BibRef
Bhayani, S.[Snehal],
Sattler, T.[Torsten],
Larsson, V.[Viktor],
Heikkilä, J.[Janne],
Kukelova, Z.[Zuzana],
Partially calibrated semi-generalized pose from hybrid point
correspondences,
WACV23(2881-2890)
IEEE DOI
2302
Estimation, Cameras, Testing, Algorithms: 3D computer vision,
Computational photography, image and video synthesis,
visual reasoning
BibRef
Höfer, T.[Timon],
Kiefer, B.[Benjamin],
Messmer, M.[Martin],
Zell, A.[Andreas],
HyperPosePDF Hypernetworks Predicting the Probability Distribution on
SO(3),
WACV23(2368-2378)
IEEE DOI
2302
Manifolds, Uncertainty, Shape, Pose estimation, Robot vision systems,
Probability density function
BibRef
Wei, W.[Wei],
Hu, J.F.[Jian-Fei],
Li, H.X.[Han-Xi],
Zuo, J.L.[Jia-Li],
Revisiting Point Matching Methods for Object Pose Estimation,
ICIVC22(325-328)
IEEE DOI
2301
Deep learning, Pose estimation, Lighting, Benchmark testing,
Task analysis, Standards, object 6DoF pose estimation, point prediction
BibRef
Huang, L.[Lin],
Hodan, T.[Tomas],
Ma, L.[Lingni],
Zhang, L.[Linguang],
Tran, L.[Luan],
Twigg, C.[Christopher],
Wu, P.C.[Po-Chen],
Yuan, J.S.[Jun-Song],
Keskin, C.[Cem],
Wang, R.[Robert],
Neural Correspondence Field for Object Pose Estimation,
ECCV22(X:585-603).
Springer DOI
2211
BibRef
Haugaard, R.L.[Rasmus Laurvig],
Buch, A.G.[Anders Glent],
SurfEmb: Dense and Continuous Correspondence Distributions for Object
Pose Estimation with Learnt Surface Embeddings,
CVPR22(6739-6748)
IEEE DOI
2210
Visualization, Computational modeling, Pose estimation, Color,
Pattern recognition, Pose estimation and tracking, Representation learning
BibRef
Ahmad, N.[Niaz],
Yoon, J.W.[Jong-Won],
StrongPose: Bottom-up and Strong Keypoint Heat Map Based Pose
Estimation,
ICPR21(8608-8615)
IEEE DOI
2105
Heating systems, Training, Location awareness, Runtime,
Pose estimation, Neural networks, Predictive models, Body heat map,
Strong key-point heat map
BibRef
Fragoso, V.[Victor],
Sinha, S.N.[Sudipta N.],
Generalized Pose-and-Scale Estimation using 4-Point Congruence
Constraints,
3DV20(1117-1126)
IEEE DOI
2102
Cameras, Pose estimation, Task analysis, Quaternions,
minimal solvers in computer vision
BibRef
Zhang, S.,
Jiang, H.,
Gu, H.,
Chen, X.,
Liu, S.,
Remote Attitude Sensing Based on High-speed Mueller Matrix Ellipsometry,
ISPRS20(B1:607-614).
DOI Link
2012
BibRef
Blanton, H.[Hunter],
Greenwell, C.[Connor],
Workman, S.[Scott],
Jacobs, N.[Nathan],
Extending Absolute Pose Regression to Multiple Scenes,
VisualSLAM20(170-178)
IEEE DOI
2008
Cameras, Training, Feature extraction, Databases,
Standards, Robot vision systems
BibRef
Zhao, W.[Wang],
Liu, S.H.[Shao-Hui],
Shu, Y.Z.[Ye-Zhi],
Liu, Y.J.[Yong-Jin],
Towards Better Generalization: Joint Depth-Pose Learning Without
PoseNet,
CVPR20(9148-9158)
IEEE DOI
2008
Recover scale, then pose.
Optical imaging, Estimation, Adaptive optics, Cameras,
Optical variables control, Training
BibRef
Snower, M.,
Kadav, A.,
Lai, F.,
Graf, H.P.,
15 Keypoints Is All You Need,
CVPR20(6737-6747)
IEEE DOI
2008
Pose estimation, Tracking, Spatial resolution, Visualization,
Task analysis, Neural networks
BibRef
Kundu, J.N.[Jogendra Nath],
Rahul, M.V.,
Ganeshan, A.[Aditya],
Babu, R.V.[R. Venkatesh],
Object Pose Estimation from Monocular Image Using Multi-view Keypoint
Correspondence,
DeepLearn-G18(III:298-313).
Springer DOI
1905
BibRef
Li, M.,
Hashimoto, K.,
Fast and Robust Pose Estimation Algorithm for Bin Picking Using Point
Pair Feature,
ICPR18(1604-1609)
IEEE DOI
1812
Mathematical model, Computational modeling, Clustering algorithms,
Robot sensing systems
BibRef
Song, J.,
Sliding window filter based unknown object pose estimation,
ICIP17(2642-2646)
IEEE DOI
1803
Cameras, Feature extraction, Pose estimation,
Smoothing methods, Trajectory,
Sliding-Window Filter
BibRef
Kim, S.A.,
Yoon, K.J.,
Point density-invariant 3D object detection and pose estimation,
ICIP17(2647-2651)
IEEE DOI
1803
Density measurement, Feature extraction, Histograms, Indexes,
Object detection, Pose estimation, 3D object detection and pose estimation
BibRef
Larsson, V.[Viktor],
Kukelova, Z.[Zuzana],
Zheng, Y.Q.[Yin-Qiang],
Making Minimal Solvers for Absolute Pose Estimation Compact and
Robust,
ICCV17(2335-2343)
IEEE DOI
1802
P4Pfr problem.
artificial intelligence, distance measurement, geometry,
image reconstruction, pose estimation, stereo image processing,
Transmission line matrix methods
BibRef
Rad, M.,
Lepetit, V.,
BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for
Predicting the 3D Poses of Challenging Objects without Using Depth,
ICCV17(3848-3856)
IEEE DOI
1802
feedforward neural nets, image classification,
image colour analysis, image segmentation, object detection,
BibRef
Lourakis, M.[Manolis],
An efficient solution to absolute orientation,
ICPR16(3816-3819)
IEEE DOI
1705
Cameras, Covariance matrices, Estimation, Position measurement,
Robots, Transmission, line, matrix, methods
BibRef
Campbell, J.[Jordan],
Mills, S.[Steven],
Paulin, M.[Mike],
Mutual information of image intensity and gradient flux for
markerless pose estimation,
ICVNZ15(1-6)
IEEE DOI
1701
particle swarm optimisation. Pose of articulated object.
BibRef
Poirson, P.[Patrick],
Ammirato, P.[Phil],
Fu, C.Y.[Cheng-Yang],
Liu, W.[Wei],
Kosecka, J.[Jana],
Berg, A.C.[Alexander C.],
Fast Single Shot Detection and Pose Estimation,
3DV16(676-684)
IEEE DOI
1701
Computational modeling
BibRef
Jaspers, H.,
Mueller, G.R.,
Wuensche, H.J.[Hans-Joachim],
High accuracy model-based object pose estimation for autonomous
recharging applications,
WACV16(1-7)
IEEE DOI
1606
Cameras
BibRef
Tulsiani, S.[Shubham],
Malik, J.[Jitendra],
Viewpoints and keypoints,
CVPR15(1510-1519)
IEEE DOI
1510
BibRef
Iversen, T.M.[Thorbjřrn Mosekjćr],
Buch, A.G.[Anders Glent],
Krüger, N.[Norbert],
Kraft, D.[Dirk],
Shape Dependency of ICP Pose Uncertainties in the Context of Pose
Estimation Systems,
CVS15(303-315).
Springer DOI
1507
BibRef
Bratanic, B.[Blaz],
Likar, B.[Bostjan],
Pernus, F.[Franjo],
Tomazevic, D.[Dejan],
Pose estimation of textureless objects in cluttered environments,
MVA15(134-137)
IEEE DOI
1507
Computer vision
BibRef
Tron, R.[Roberto],
Daniilidis, K.[Kostas],
Statistical Pose Averaging with Non-isotropic and Incomplete Relative
Measurements,
ECCV14(V: 804-819).
Springer DOI
1408
BibRef
Kneip, L.[Laurent],
Li, H.D.[Hong-Dong],
Seo, Y.D.[Yong-Duek],
UPnP: An Optimal O(n) Solution to the Absolute Pose Problem with
Universal Applicability,
ECCV14(I: 127-142).
Springer DOI
1408
BibRef
Sweeney, C.[Chris],
Flynn, J.[John],
Turk, M.[Matthew],
Solving for Relative Pose with a Partially Known Rotation is a
Quadratic Eigenvalue Problem,
3DV14(483-490)
IEEE DOI
1503
Cameras
BibRef
Sweeney, C.[Chris],
Fragoso, V.[Victor],
Höllerer, T.[Tobias],
Turk, M.[Matthew],
Large Scale SfM with the Distributed Camera Model,
3DV16(230-238)
IEEE DOI
1701
BibRef
Earlier:
gDLS: A Scalable Solution to the Generalized Pose and Scale Problem,
ECCV14(IV: 16-31).
Springer DOI
1408
BibRef
Kobayashi, T.,
Kato, H.,
Yanagihara, H.,
Novel Keypoint Registration for Fast and Robust Pose Detection on
Mobile Phones,
ACPR13(266-271)
IEEE DOI
1408
augmented reality
BibRef
Xiao, Y.[Yi],
Lu, H.C.[Hu-Chuan],
Li, S.F.[Shi-Feng],
Posterior constraints for double-counting problem in clustered pose
estimation,
ICIP12(5-8).
IEEE DOI
1302
BibRef
Dondera, R.[Radu],
Davis, L.S.[Larry S.],
Kernel PLS regression for robust monocular pose estimation,
MLVMA11(24-30).
IEEE DOI
1106
Evaluate five regression techniques for monocular 3D pose estimation.
BibRef
Xu, W.[Wei],
Mulligan, J.[Jane],
Robust relative pose estimation with integrated cheirality constraint,
ICPR08(1-4).
IEEE DOI
0812
RANSAC based pose
BibRef
Alhwarin, F.[Faraj],
Ristic-Durrant, D.[Danijela],
Gräser, A.[Axel],
VF-SIFT: Very Fast SIFT Feature Matching,
DAGM10(222-231).
Springer DOI
1009
BibRef
Vuppala, S.K.[Sai Krishna],
Gräser, A.[Axel],
An Approach for Tracking the 3D Object Pose Using Two Object Points,
CVS08(xx-yy).
Springer DOI
0805
BibRef
Yang, M.[Ming],
Yu, Q.[Qian],
Wang, H.[Hong],
Zhang, B.[Bo],
Vision based real-time pose estimation for intelligent vehicles,
IVS04(262-267).
IEEE DOI
0411
Ground plane assumption.
Gradient Angle Histogram.
BibRef
Yang, M.[Ming],
Dong, B.[Bin],
Wang, H.[Hong],
Zhang, B.[Bo],
Real-time pose estimation for outdoor, mobile robots using range data,
ICPR02(II: 593-596).
IEEE DOI
0211
BibRef
Ude, A.[Ales],
Nonlinear Least Squares Optimisation of Unit Quaternion Functions for
Pose Estimation from Corresponding Features,
ICPR98(Vol I: 425-427).
IEEE DOI
9808
BibRef
Jacobs, D.W.,
Optimal Matching of Planar Models in 3D Scenes,
CVPR91(269-274).
IEEE DOI Point features on a flat object to point features in 3-D in an
arbitrary pose. Newer: oriented points require more space
in the indexing scheme.
BibRef
9100
Hel-Or, Y., and
Werman, M.,
Absolute Orientation from Uncertain Point Data: A Unified Approach,
CVPR92(77-82).
IEEE DOI Pose using a model, predicted 3-D from 2-D
BibRef
9200
Wang, Z.,
Jepson, A.D.,
A New Closed-Form Solution for Absolute Orientation,
CVPR94(129-134).
IEEE DOI
BibRef
9400
Lu, L.[Liu],
Luo, F.[Fang],
Mulder, N.J.,
Recognition of 2-D Objects by Optimal Matching,
BMVC94(xx-yy).
PDF File.
9409
BibRef
Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Point Pattern Invariants .