12.3.4.3 Pose Estimation -- Range Data

Chapter Contents (Back)
Matching, Range Data. Pose Estimation, Range Data.

Walas, K.[Krzysztof], Leonardis, A.[Aleš],
UoB highly occluded object challenge (UoB-HOOC),
2016
WWW Link. Dataset, Object Detection. BibRef

Faugeras, O.D., and Hebert, M.,
The Representation, Recognition, and Locating of 3-D Objects,
IJRR(5), No. 3, Fall 1986, pp. 27-52. BibRef 8600
Earlier:
The Representation, Recognition, and Positioning of 3-D Shapes from Range Data,
T3DMP86(13-51). BibRef
Earlier: 3DMV87(301-353). BibRef
And:
A 3-D Recognition and Positing Algorithm Using Geometrical Matching Between Primitive Surfaces,
IJCAI83(996-1002). Recognize Three-Dimensional Objects. Range finder input and a detailed 3-D model (base on range finder data). Match model and image. BibRef

Faugeras, O.D., Hebert, M., Pauchon, E., and Ponce, J.,
Object Representation, Identification, and Positioning from Range Data,
RR-IS84(425-446). BibRef 8400

Faugeras, O.D., Hebert, M., and Pauchon, E.,
Segmentation of Range Data into Planar and Quadratic Patches,
CVPR83(8-13). BibRef 8300

Hebert, M., Kanade, T.,
First Results on Outdoor Scene Analysis Using Range Data,
DARPA85(224-231). BibRef 8500

Hebert, M.,
3-D Landmark Recognition from Range Images,
CVPR92(360-365).
IEEE DOI BibRef 9200

Cole, R., Yap, C.K.,
Shape from Probing,
Algorithms(8), 1987, pp. 19-38. BibRef 8700

Quek, F., Jain, R.C., and Weymouth, T.E.,
An Abstraction-Based Approach to 3-D Pose Determination from Range Images,
PAMI(15), No. 7, July 1993, pp. 722-736.
IEEE DOI Abstraction means feature-based. Compute features of the curves for use in the pose estimation. BibRef 9307

Zhuang, X.H.[Xin-Hua], Huang, Y.[Yan],
Robust 3-D 3-D Pose Estimation,
PAMI(16), No. 8, August 1994, pp. 818-824.
IEEE DOI BibRef 9408
Earlier: ICCV93(567-571).
IEEE DOI BibRef

Burtnyk, N.[Nestor], Greenspan, M.A.[Michael A.],
System for determining the pose of an object which utilizes range profiles and synethic profiles derived from a model,
US_Patent5,471,541, Nov 28, 1995
WWW Link. BibRef 9511

Lavallée, S.[Stéphane], Szeliski, R.S.[Richard S.],
Recovering the Position and Orientation of Free-Form Objects from Image Contours Using 3D Distance Maps,
PAMI(17), No. 4, April 1995, pp. 378-390.
IEEE DOI Octree. Match 3D images (MRI or CT) with 2D X-Ray projections accurately and quickly. Applied to computer assisted surgery. BibRef 9504

Szeliski, R.S.[Richard S.], Lavallée, S.[Stéphane],
Matching 3-D Anatomical Surfaces with Non-Rigid Deformations Using Octree-Splines,
IJCV(18), No. 2, May 1996, pp. 171-186.
Springer DOI 9608
BibRef

Brunie, L.[Lionel], Lavallee, S.[Stephane], Szeliski, R.S.[Richard S.],
Using Force Fields Derived from 3D Distance Maps for Inferring the Attitude of a 3D Rigid Object,
ECCV92(670-675).
Springer DOI BibRef 9200

Lavallee, S.[Stephane], Szeliski, R.S.[Richard S.], Brunie, L.[Lionel],
Matching 3-D Smooth Surfaces with Their 2-D Projections Using 3-D Distance Maps,
SPIE(1570), 1991, pp. 322-336 BibRef 9100

Champleboux, G., Lavallee, S., Szeliski, R.S., and Brunie, L.,
From Accurate Range Imaging Sensor Calibration to Accurate Model-Based 3-D Object Localization,
CVPR92(83-89).
IEEE DOI Match 3-D point data and derive the pose. BibRef 9200

Kemmotsu, K., and Kanade, T.,
Uncertainty in Object Pose Determination with Three Light-Stripe Range Measurements,
RA(11), No. 5, October 1995, pp. 741-747. BibRef 9510
Earlier: CMU-CS-TR-93-100, CMU CS Dept., January 1993. BibRef
And:
Sensor Placement Design for Object Pose Determination with Three Light-Stripe Range Finders,
CMU-CS-TR-94-152, 1994.
PS File. Matching 3-D light-stripe generated images to get the pose. BibRef

Stoddart, A.J., Lemke, S., Hilton, A., Renn, T.,
Estimating Pose Uncertainty for Surface Registration,
IVC(16), No. 2, February 20 1998, pp. 111-120.
WWW Link. 9803
BibRef
Earlier: BMVC96(Matching Surfaces). 9608
University of Surrey BibRef

Sanchiz, J.M.[Jose M.], Fisher, R.B.[Robert Burns],
Viewpoint Estimation in Three-Dimensional Images Taken with Perspective Range Sensors,
PAMI(22), No. 11, November 2000, pp. 1324-1329.
IEEE DOI 0012
BibRef EdinburghFrom 3-D of points of known topology (with noise) BibRef

Greenspan, M.A.[Michael A.],
Geometric Probing of Dense Range Data,
PAMI(24), No. 4, April 2002, pp. 495-508.
IEEE DOI 0204
Pose determination. Hypothesize the pose, search for confirmation. Geometric Probing: See also Shape from Probing. BibRef

Greenspan, M.A.[Michael A.],
Geometric Probing for 3D Object Recognition in Dense Range Data,
Ph.D.Thesis, Carleton Univ., 1999. BibRef 9900

Lucchese, L.[Luca],
A Frequency Domain Technique Based on Energy Radial Projections for Robust Estimation of Global 2D Affine Transformations,
CVIU(81), No. 1, January 2001, pp. 72-116.
DOI Link 0102
BibRef
And: Corrections: CVIU(82), No. 1, April 2001, pp. 82-83.
DOI Link 0104
BibRef
Earlier:
Estimating Affine Transformations in the Frequency Domain,
ICIP01(II: 909-912).
IEEE DOI 0108
BibRef

Lucchese, L.,
Closed-form pose estimation from metric rectification of coplanar points,
VISP(153), No. 3, June 2006, pp. 364-378.
DOI Link 0608
See also Frequency Domain Technique for Range Data Registration, A. BibRef

Lucchese, L.,
A Hybrid Frequency-space Domain Algorithm for Estimating Projective Transformations of Color Images,
ICIP01(II: 913-916).
IEEE DOI 0108
BibRef

Ünsalan, C.[Cem],
A model based approach for pose estimation and rotation invariant object matching,
PRL(28), No. 1, 1 January 2007, pp. 49-57.
WWW Link. 0611
Pose estimation; Shape alignment; Object matching; Implicit polynomials BibRef

Fujimura, K.[Kikuo], Zhu, Y.D.[You-Ding],
Pose estimation based on critical point analysis,
US_Patent7,317,836, Jan 8, 2008
WWW Link. BibRef 0801

Laga, H.[Hamid],
Data-driven approach for automatic orientation of 3D shapes,
VC(27), No. 11, November 2011, pp. 977-989.
WWW Link. 1112
BibRef

Laga, H.[Hamid],
Graspable Parts Recognition in Man-Made 3D Shapes,
ACCV12(II:552-564).
Springer DOI 1304
BibRef

Xia, J.Y.[Jun-Ying], Xu, X.Q.[Xiao-Quan], Zhang, Q.[Qi], Xiong, J.L.[Jiu-Long],
Speeding Up the Orthogonal Iteration Pose Estimation,
IEICE(E95-D), No. 7, July 2012, pp. 1827-1829.
WWW Link. 1208
BibRef

Mooser, R.[René], Forsberg, F.[Fredrik], Hack, E.[Erwin], Székely, G.[Gábor], Sennhauser, U.[Urs],
Estimation of affine transformations directly from tomographic projections in two and three dimensions,
MVA(24), No. 2, February 2013, pp. 419-434.
WWW Link. 1302
Orientations from projections not reconstruction BibRef

Hu, J.X.[Jia-Xi], Hua, J.[Jing],
Pose analysis using spectral geometry,
VC(29), No. 9, September 2013, pp. 949-958.
WWW Link. 1307
3D models represented by meshes. Use spectrum domain defined by Laplace-Beltrami operator. BibRef

Papadakis, P.[Panagiotis],
Enhanced pose normalization and matching of non-rigid objects based on support vector machine modelling,
PR(47), No. 1, 2014, pp. 216-227.
Elsevier DOI 1310
Non-rigid analysis BibRef

Papadakis, P.[Panagiotis], Pirri, F.[Fiora],
Consistent pose normalization of non-rigid shapes using One-Class Support Vector Machines,
NORDIA11(23-30).
IEEE DOI 1106
BibRef

Wang, W.[Wei], Chen, L.[Lili], Liu, Z.[Ziyuan], Kühnlenz, K.[Kolja], Kühnlenz, K.[Kolja], Burschka, D.[Darius],
Textured/textureless object recognition and pose estimation using RGB-D image,
RealTimeIP(10), No. 4, December 2015, pp. 667-682.
Springer DOI 1512
BibRef

Silva do Monte Lima, J.P.[Joăo Paulo], Simőes, F.P.M.[Francisco Paulo Magalhăes], Uchiyama, H.[Hideaki], Teichrieb, V.[Veronica], Marchand, E.[Eric],
Depth-assisted rectification for real-time object detection and pose estimation,
MVA(27), No. 2, February 2016, pp. 193-219.
Springer DOI 1602
BibRef

Oumer, N.W.[Nassir W.], Kriegel, S.[Simon], Ali, H.[Haider], Reinartz, P.[Peter],
Appearance learning for 3D pose detection of a satellite at close-range,
PandRS(125), No. 1, 2017, pp. 1-15.
Elsevier DOI 1703
Satellite pose detection BibRef


Rink, C.[Christian], Kriegel, S.[Simon],
Streaming Monte Carlo Pose Estimation for Autonomous Object Modeling,
CRV16(156-163)
IEEE DOI 1612
3D modeling; Active sensing; Laser scanning; Pose estimation BibRef

Basevi, H.[Hector], Leonardis, A.[Aleš],
Towards Categorization and Pose Estimation of Sets of Occluded Objects in Cluttered Scenes from Depth Data and Generic Object Models Using Joint Parsing,
6DPose16(III: 665-681).
Springer DOI 1611
BibRef

Zamir, A.R.[Amir R.], Wekel, T.[Tilman], Agrawal, P.[Pulkit], Wei, C.[Colin], Malik, J.[Jitendra], Savarese, S.[Silvio],
Generic 3D Representation via Pose Estimation and Matching,
ECCV16(III: 535-553).
Springer DOI 1611
BibRef

Srinivasan, R.R.[Ranga Ramanujam], Xia, Z.Y.[Zheng-Yu], Kim, J.[Joohee], Park, Y.S.[Young Soo],
Confidence indicators based pose estimation for high-quality 3D reconstruction using depth image,
VCIP15(1-4)
IEEE DOI 1605
Anisotropic magnetoresistance BibRef

Papon, J.[Jeremie], Schoeler, M.[Markus],
Semantic Pose Using Deep Networks Trained on Synthetic RGB-D,
ICCV15(774-782)
IEEE DOI 1602
Furniture, indoor. Adaptation models BibRef

Mottaghi, R.[Roozbeh], Xiang, Y.[Yu], Savarese, S.[Silvio],
A coarse-to-fine model for 3D pose estimation and sub-category recognition,
CVPR15(418-426)
IEEE DOI 1510
BibRef

Zach, C.[Christopher], Penate-Sanchez, A.[Adrian], Pham, M.T.[Minh-Tri],
A dynamic programming approach for fast and robust object pose recognition from range images,
CVPR15(196-203)
IEEE DOI 1510
BibRef

Großmann, B.[Bjarne], Siam, M.[Mennatullah], Krüger, V.[Volker],
Comparative Evaluation of 3D Pose Estimation of Industrial Objects in RGB Pointclouds,
CVS15(329-342).
Springer DOI 1507
BibRef

Nguyen, D.D.[Duc Dung], Ko, J.P.[Jae Pil], Jeon, J.W.[Jae Wook],
Determination of 3D object pose in point cloud with CAD model,
FCV15(1-6)
IEEE DOI 1506
feature extraction BibRef

Shimizu, S., Koyasu, H., Kobayashi, Y., Kuno, Y.,
Object pose estimation using category information from a single image,
FCV15(1-4)
IEEE DOI 1506
computer vision BibRef

Andreux, M.[Mathieu], Rodolŕ, E.[Emanuele], Aubry, M.[Mathieu], Cremers, D.[Daniel],
Anisotropic Laplace-Beltrami Operators for Shape Analysis,
NORDIA14(299-312).
Springer DOI 1504
BibRef

Guzman-Rivera, A.[Abner], Kohli, P.[Pushmeet], Glocker, B.[Ben], Shotton, J.[Jamie], Sharp, T.[Toby], Fitzgibbon, A.[Andrew], Izadi, S.[Shahram],
Multi-output Learning for Camera Relocalization,
CVPR14(1114-1121)
IEEE DOI 1409
Multi-output learning; camera relocalization; diverse predictions The pose of a camera relative to a known 3D scene with RGB-D image. BibRef

Shotton, J.D.J.[Jamie D.J.], Glocker, B.[Ben], Zach, C.[Christopher], Izadi, S.[Shahram], Criminisi, A.[Antonio], Fitzgibbon, A.[Andrew],
Scene Coordinate Regression Forests for Camera Relocalization in RGB-D Images,
CVPR13(2930-2937)
IEEE DOI 1309
Infer pose relative to known 3D scene. See also TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context. BibRef

Barnea, E.[Ehud], Ben-Shahar, O.[Ohad],
Depth Based Object Detection from Partial Pose Estimation of Symmetric Objects,
ECCV14(V: 377-390).
Springer DOI 1408
Partial pose from depth, match. BibRef

Breslav, M.[Mikhail], Hedrick, T.L., Sclaroff, S.[Stan], Betke, M.[Margrit],
Discovering useful parts for pose estimation in sparsely annotated datasets,
WACV16(1-9)
IEEE DOI 1606
Animals BibRef

Breslav, M.[Mikhail], Fuller, N.[Nathan], Sclaroff, S.[Stan], Betke, M.[Margrit],
3D pose estimation of bats in the wild,
WACV14(91-98)
IEEE DOI 1406
Cameras BibRef

Zhai, D.[Deming], Chang, H.[Hong], Chen, X.L.[Xi-Lin], Gao, W.[Wen],
Instance-specific canonical correlation analysis for pose alignment,
ICIP13(2544-2547)
IEEE DOI 1402
BibRef

Kurmankhojayev, D.[Daniyar], Hasler, N.[Nils], Theobalt, C.[Christian],
Monocular Pose Capture with a Depth Camera Using a Sums-of-Gaussians Body Model,
GCPR13(415-424).
Springer DOI 1311
BibRef

Thachasongtham, D.[Dissaphong], Yoshida, T.[Takumi], de Sorbier, F.[François], Saito, H.[Hideo],
3D Object Pose Estimation Using Viewpoint Generative Learning,
SCIA13(512-521).
Springer DOI 1311
BibRef

El-Gaaly, T.[Tarek], Torki, M.[Marwan],
RGBD object pose recognition using local-global multi-kernel regression,
ICPR12(2468-2471).
WWW Link. 1302
BibRef

Produit, T.[Timothee], Tuia, D.[Devis], Golay, F.[Francois], Strecha, C.[Christoph],
Pose estimation of landscape images using DEM and orthophotos,
CVRS12(209-214).
IEEE DOI 1302
BibRef

Raytchev, B.[Bisser], Terakado, K.[Kazuya], Tamaki, T.[Toru], Kaneda, K.[Kazufumi],
Pose estimation by local procrustes regression,
ICIP11(3585-3588).
IEEE DOI 1201
BibRef

Axenopoulos, A.[Apostolos], Litos, G.[Georgios], Daras, P.[Petros],
3D model retrieval using accurate pose estimation and view-based similarity,
ICMR11(41).
DOI Link 1301
3D model alignment method, combining two criteria, the plane reflection symmetry and rectilinearity. BibRef

Zhang, Q.[Qian], Jia, J.Y.[Jin-Yuan],
A GPU Based High-Efficient And Accurate Optimal Pose Alignment Approach Of 3d Objects,
3DOR11(97-100)
DOI Link 1301
BibRef

Fenzi, M.[Michele], Leal-Taixe, L.[Laura], Ostermann, J.[Jorn], Tuytelaars, T.,
Continuous Pose Estimation with a Spatial Ensemble of Fisher Regressors,
ICCV15(1035-1043)
IEEE DOI 1602
Design automation BibRef

Fenzi, M.[Michele], Leal-Taixe, L.[Laura], Schindler, K.[Konrad], Ostermann, J.[Jorn],
Pose Estimation of Object Categories in Videos Using Linear Programming,
WACV15(821-828)
IEEE DOI 1503
Estimation BibRef

Fenzi, M.[Michele], Ostermann, J.[Jorn],
Embedding Geometry in Generative Models for Pose Estimation of Object Categories,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Fenzi, M.[Michele], Leal-Taixe, L.[Laura], Rosenhahn, B.[Bodo], Ostermann, J.[Jorn],
Class Generative Models Based on Feature Regression for Pose Estimation of Object Categories,
CVPR13(755-762)
IEEE DOI 1309
Continuous pose estimation BibRef

Soltow, E.[Erik], Rosenhahn, B.[Bodo],
Automatic Pose Estimation Using Contour Information from X-Ray Images,
MCBMIIA15(246-257).
Springer DOI 1603
BibRef

Fenzi, M.[Michele], Dragon, R.[Ralf], Leal-Taixé, L.[Laura], Rosenhahn, B.[Bodo], Ostermann, J.[Jörn],
3d Object Recognition and Pose Estimation for Multiple Objects Using Multi-Prioritized Ransac and Model Updating,
DAGM12(123-133).
Springer DOI 1209
BibRef

Persad, R.A., Armenakis, C., Sohn, G.,
Integration of Video Images and Cad Wireframes for 3d Object Localization,
AnnalsPRS(I-3), No. 2012, pp. 353-358.
HTML Version. 1209
BibRef

Ali, H.[Haider], Figueroa, N.[Nadia],
Segmentation and Pose Estimation of Planar Metallic Objects,
CRV12(376-382).
IEEE DOI 1207
Segmentation by euclidean clustering, pose estimation by ICP. Planar surfaces in laser scanner data. BibRef

Aldoma, A., Vincze, M.,
Pose Alignment for 3D Models and Single View Stereo Point Clouds Based on Stable Planes,
3DIMPVT11(374-380).
IEEE DOI 1109
BibRef

Bey, A.[Aurélien], Chaine, R.[Raphaëlle], Marc, R.[Raphaël], Thibault, G.[Guillaume], Akkouche, S.[Samir],
Reconstruction of Consistent 3D CAD Models from Point Cloud Data Using A Priori CAD Models,
Laser11(xx-yy).
DOI Link 1109
Fitting the point cloud with the 3D model. BibRef

Jia, H.J.[Hong-Jun], Wu, G.R.[Guo-Rong], Wang, Q.[Qian], Shen, D.G.[Ding-Gang],
ABSORB: Atlas building by Self-Organized Registration and Bundling,
CVPR10(2785-2790).
IEEE DOI 1006
Register the model by deforming to each subject. BibRef

Hebel, M., Arens, M., Stilla, U.,
Utilization of 3D City Models and Airborne Laser Scanning for Terrain-based Navigation of Helicopters and UAVs,
CMRT09(187-192).
PDF File. 0909
Use 3D models to determine location. BibRef

Selby, B.P., Sakas, G., Walter, S., Groch, W.D., Stilla, U.,
Detection of Pose Changes for Spatial Objects from Projective Images,
PIA07(105).
PDF File. 0711
BibRef

Guđmundsson, S.Á.[Sigurjón Árni], Larsen, R.[Rasmus], Ersbřll, B.K.[Bjarne K.],
Robust Pose Estimation Using the SwissRanger SR-3000 Camera,
SCIA07(968-975).
Springer DOI 0706
classify and pose from low res model and 3D data. BibRef

Rodgers, J.[Jim], Anguelov, D.[Dragomir], Pang, H.C.[Hoi-Cheung], Koller, D.[Daphne],
Object Pose Detection in Range Scan Data,
CVPR06(II: 2445-2452).
IEEE DOI 0606
BibRef

Sepp, W., Hirzinger, G.,
Featureless 6 DoF pose refinement from stereo images,
ICPR02(IV: 17-20).
IEEE DOI 0211
BibRef

Rui, L., Hirzinger, G.[Gerd],
Marker-Free Automatic Matching Of Range Data,
PanoPhot05(xx-yy).
PDF File. 0502
BibRef

Amano, T., Hiura, S., Yamaguchi, A., Inokuchi, S.,
Eigenispace Approach for a Pose Detection with Range Images: Robust Pose Detection Method for Pixel Lacks of Range Images,
ICPR96(I: 622-626).
IEEE DOI 9608
(Osaka Univ., J) BibRef

Beveridge, J.R.[J. Ross], and Schwickerath, A.N.A.[Anthony N.A.],
Object to Multisensor Coregistration with Eight Degrees of Freedom,
ARPA94(I:481-490).
PS File. BibRef 9400

Schwickerath, A.N.A.[Anthony N.A.], Beveridge, J.R.[J. Ross],
Coregistration of Range and Optical Images Using Coplanarity and Orientation Constraints,
CVPR96(899-906).
IEEE DOI
PS File. BibRef 9600

Schwickerath, A.N.A., Beveridge, J.R.,
Coregistering 3D Models, Range, and Optical Imagery Using Least-Median Squares Fitting,
ARPA96(719-722).
PS File. BibRef 9600

Pipitone, F., Adams, W.,
Rapid recognition of freeform objects in noisy range images using tripod operators,
CVPR93(715-716).
IEEE DOI 0403
BibRef


Last update:May 25, 2017 at 22:18:08