Shih, S.W.[Sheng-Wen],
Yu, T.Y.[Tzu-Yi],
On designing an isotropic fiducial mark,
IP(12), No. 9, September 2003, pp. 1054-1066.
IEEE DOI
0308
BibRef
Wiles, A.D.,
Likholyot, A.,
Frantz, D.D.,
Peters, T.M.,
A Statistical Model for Point-Based Target Registration Error With
Anisotropic Fiducial Localizer Error,
MedImg(27), No. 3, March 2008, pp. 378-390.
IEEE DOI
0803
BibRef
Wiles, A.D.,
Peters, T.M.,
Real-Time Estimation of FLE Statistics for 3-D Tracking With
Point-Based Registration,
MedImg(28), No. 9, September 2009, pp. 1384-1398.
IEEE DOI
0909
FLE: Fiducial Localizer Error
BibRef
Wiles, A.D.,
Peters, T.M.,
Target Tracking Errors for 5D and 6D Spatial Measurement Systems,
MedImg(29), No. 3, March 2010, pp. 879-894.
IEEE DOI
1003
5D from magnetic tracking system (XYZ, 2 rotations), combine 2 to get 6D.
But not as exact as optical methods.
BibRef
Hamsici, O.C.[Onur C.],
Martinez, A.M.[Aleix M.],
Rotation Invariant Kernels and Their Application to Shape Analysis,
PAMI(31), No. 11, November 2009, pp. 1985-1999.
IEEE DOI
0910
BibRef
And:
Active Appearance Models with Rotation Invariant Kernels,
ICCV09(1003-1009).
IEEE DOI
0909
Normalize shape vectors with respect to their mean and norm.
See also Bayes Optimality in Linear Discriminant Analysis.
BibRef
Benitez-Quiroz, C.F.,
Rivera, S.[Samuel],
Gotardo, P.F.U.[Paulo F.U.],
Martinez, A.M.[Aleix M.],
Salient and non-salient fiducial detection using a probabilistic
graphical model,
PR(47), No. 1, 2014, pp. 208-215.
Elsevier DOI
1310
Shape modeling. Faces, hands, cardiac structures.
BibRef
Rivera, S.[Samuel],
Martinez, A.M.[Aleix M.],
Learning deformable shape manifolds,
PR(45), No. 4, 2012, pp. 1792-1801.
Elsevier DOI
1410
Shape modeling
BibRef
Fiala, M.[Mark],
Designing Highly Reliable Fiducial Markers,
PAMI(32), No. 7, July 2010, pp. 1317-1324.
IEEE DOI
1006
BibRef
Earlier:
ARTag: a Fiducial Marker System Using Digital Techniques,
CVPR05(II: 590-596).
IEEE DOI
0507
Special markers in image for alignment for AR applications.
BibRef
Ross, R.[Robert],
Martchenko, A.[Andrew],
Devlin, J.[John],
A 3-degree of freedom binary search pose estimation technique,
MVA(24), No. 4, May 2013, pp. 769-776.
Springer DOI
1304
three fiduciary marker points. motor vehicle pose.
Compare to POSIT
See also Iterative Pose Estimation Using Coplanar Feature Points.
BibRef
Bergamasco, F.[Filippo],
Albarelli, A.[Andrea],
Torsello, A.[Andrea],
Pi-Tag: a fast image-space marker design based on projective invariants,
MVA(24), No. 6, August 2013, pp. 1295-1310.
WWW Link.
1307
BibRef
Earlier:
Image-Space Marker Detection and Recognition Using Projective
Invariants,
3DIMPVT11(381-388).
IEEE DOI
1109
BibRef
Bergamasco, F.[Filippo],
Albarelli, A.[Andrea],
Rodola, E.[Emanuele],
Torsello, A.[Andrea],
RUNE-Tag: A high accuracy fiducial marker with strong occlusion
resilience,
CVPR11(113-120).
IEEE DOI
1106
BibRef
Cui, X.N.[Xue-Nan],
Kim, H.[Hakil],
Park, E.[Eunsoo],
Choi, H.H.[Hyo-Hoon],
Robust and accurate pattern matching in fuzzy space for fiducial mark
alignment,
MVA(24), No. 3, April 2013, pp. 447-459.
WWW Link.
1303
BibRef
Bagherinia, H.[Homayoun],
Manduchi, R.[Roberto],
Robust real-time detection of multi-color markers on a cell phone,
RealTimeIP(8), No. 2, June 2013, pp. 207-223.
WWW Link.
1306
BibRef
Garrido-Jurado, S.,
Muñoz-Salinas, R.,
Madrid-Cuevas, F.J.,
Marín-Jiménez, M.J.,
Automatic generation and detection of highly reliable fiducial
markers under occlusion,
PR(47), No. 6, 2014, pp. 2280-2292.
Elsevier DOI
1403
Award, Pattern Recognition, Honorable Mention. Augmented reality
BibRef
Garrido-Jurado, S.,
Muñoz-Salinas, R.,
Madrid-Cuevas, F.J.,
Medina-Carnicer, R.,
Generation of fiducial marker dictionaries using Mixed Integer Linear
Programming,
PR(51), No. 1, 2016, pp. 481-491.
Elsevier DOI
1601
Fiducial markers
BibRef
Maidi, M.[Madjid],
Ababsa, F.[Fakhr_Eddine],
Mallem, M.[Malik],
Preda, M.[Marius],
Hybrid tracking system for robust fiducials registration in augmented
reality,
SIViP(9), No. 4, May 2015, pp. 831-849.
Springer DOI
1504
BibRef
Maidi, M.[Madjid],
Ababsa, F.[Fakhr_Eddine],
Mallem, M.[Malik],
Vision-inertial tracking system for robust fiducials registration in
augmented reality,
CIMSVP09(83-90).
IEEE DOI
0903
BibRef
Ababsa, F.E.,
Roussel, D.,
Mallem, M.,
Didier, J.Y.,
2D/3D automatic matching technique for 3D recovering of free form
objects,
ICPR02(II: 430-433).
IEEE DOI
0211
BibRef
Cruz-Hernández, H.[Heriberto],
de la Fraga, L.G.[Luis Gerardo],
A fiducial tag invariant to rotation, translation, and perspective
transformations,
PR(81), 2018, pp. 213-223.
Elsevier DOI
1806
Order Type, Computational geometry, Visual fiducial tag,
Point pattern matching, Automatic identification, Computer vision
BibRef
Romero-Ramirez, F.J.[Francisco J.],
Muñoz-Salinas, R.[Rafael],
Medina-Carnicer, R.[Rafael],
Speeded up detection of squared fiducial markers,
IVC(76), 2018, pp. 38-47.
Elsevier DOI
1808
Fiducial markers, Marker mapping, SLAM
BibRef
Qiu, L.,
Zhang, Y.,
Xu, L.,
Niu, X.,
Zhang, Q.,
Zhang, L.,
Estimating Maximum Target Registration Error Under Uniform
Restriction of Fiducial Localization Error in Image Guided System,
MedImg(37), No. 4, April 2018, pp. 881-892.
IEEE DOI
1804
Estimation, Monte Carlo methods, Navigation, Optimization, Surgery,
maximum target registration error estimation
BibRef
Benligiray, B.[Burak],
Topal, C.[Cihan],
Akinlar, C.[Cuneyt],
STag: A stable fiducial marker system,
IVC(89), 2019, pp. 158-169.
Elsevier DOI
1909
Fiducial markers, Pose estimation stability,
Geometric calibration, Mixed reality
BibRef
Hajjami, J.,
Caracotte, J.,
Caron, G.,
Napoléon, T.,
ArUcOmni: detection of highly reliable fiducial markers in panoramic
images,
OmniCV20(2693-2699)
IEEE DOI
2008
Cameras, Pose estimation, Sensors,
Mathematical model, Reliability
BibRef
Uchiyama, H.[Hideaki],
Oyamada, Y.J.[Yu-Ji],
Transparent Random Dot Markers,
ICPR18(254-259)
IEEE DOI
1812
Shape, Indexes, Histograms, Robustness, User interfaces.
BibRef
Ferrão, J.[José],
Dias, P.[Paulo],
Neves, A.J.R.[António J. R.],
Detection of Aruco Markers Using the Quadrilateral Sum Conjuncture,
ICIAR18(363-369).
Springer DOI
1807
BibRef
de Gol, J.[Joseph],
Bretl, T.[Timothy],
Hoiem, D.[Derek],
ChromaTag: A Colored Marker and Fast Detection Algorithm,
ICCV17(1481-1490)
IEEE DOI
1802
Fiducial markers.
image colour analysis, object detection, ChromaTag, colored marker,
false positive rejection, fast detection algorithm,
Robustness
BibRef
Mondéjar-Guerra, V.M.[Víctor Manuel],
Garrido-Jurado, S.[Sergio],
Muñoz-Salinas, R.[Rafael],
Marín-Jiménez, M.J.[Manuel J.],
Medina-Carnicer, R.[Rafael],
Classification of Fiducial Markers in Challenging Conditions with SVM,
IbPRIA17(344-352).
Springer DOI
1706
BibRef
Edwards, M.J.,
Hayes, M.P.,
Green, R.D.,
High-accuracy fiducial markers for ground truth,
ICVNZ16(1-6)
IEEE DOI
1701
Cameras
BibRef
Calvet, L.,
Gurdjos, P.,
Griwodz, C.,
Gasparini, S.,
Detection and Accurate Localization of Circular Fiducials under
Highly Challenging Conditions,
CVPR16(562-570)
IEEE DOI
1612
BibRef
Khan, D.,
Ullah, S.,
Rabbi, I.,
Optimality of black to white ratio and information complexity for
robust marker recognition,
IPTA14(1-6)
IEEE DOI
1503
augmented reality
BibRef
Xu, A.Q.[An-Qi],
Dudek, G.[Gregory],
Fourier Tag: A Smoothly Degradable Fiducial Marker System with
Configurable Payload Capacity,
CRV11(40-47).
IEEE DOI
1105
BibRef
dos Anjos, A.[Antonio],
Shahbazkia, H.R.[Hamid Reza],
Automatic marker detection for blob images,
WACV09(1-6).
IEEE DOI
0912
BibRef
Heimonen, T.[Teuvo],
Heikkilä, J.[Janne],
Monocular Point Based Pose Estimation of Artificial Markers by Using
Evolutionary Computing,
SCIA07(122-131).
Springer DOI
0706
BibRef
Rugis, J.[John],
Klette, R.[Reinhard],
Surface Registration Markers from Range Scan Data,
IWCIA06(430-444).
Springer DOI
0606
BibRef
Claus, D.[David],
Fitzgibbon, A.W.[Andrew W.],
Reliable Automatic Calibration of a Marker-Based Position Tracking
System,
WACV05(I: 300-305).
IEEE DOI
0502
BibRef
Claus, D.[David],
Fitzgibbon, A.W.[Andrew W.],
Reliable Fiducial Detection in Natural Scenes,
ECCV04(Vol IV: 469-480).
Springer DOI
0405
BibRef
Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Generic Object Detection .