12.3.4.2 Range Data Matching -- Accumulation Methods

Krighnapuran, R.[Raghu], and Casasent, D.[David],
Determination of Three Dimensional Object Location and Orientation from Range Data,
PAMI(11), No. 11, November 1989, pp. 1158-1167.
IEEE Abstract.
WWW Version. Hough. Pose estimation from 3D views and an extension of the Hough transform. BibRef 8911

Xuan, J., Wang, Y., Zheng, Q., Adali, T.,
Discontinuity-Embedded Deformable Models for Surface Reconstruction From Range Images,
SPLetters(12), No. 12, December 2005, pp. 805-808.
IEEE DOI Link 0512
BibRef

Xuan, J., Wang, Y., Adali, T., Zheng, Q., Hayes, W., Freedman, M.T., Mun, S.K.,
A Deformable Surface-Spine Model for 3-D Surface Registration,
ICIP97(III: 236-239).
IEEE DOI Link BibRef 9700

Wheeler, M.D.[Mark D.], Sato, Y.[Yoichi], and Ikeuchi, K.[Katsushi],
Consensus Surfaces for Modeling 3D Objects from Multiple Range Images,
ICCV98(917-924).
IEEE DOI Link BibRef 9800
And: MfR01(Chapter I-3). BibRef
And: DARPA97(911-920). BibRef

Rohling, R.[Robert], Gee, A.H.[Andrew H.], and Berman, L.H.[Laurence H.],
Automatic Registration of 3-D Ultrasound Images,
ICCV98(298-303).
IEEE DOI Link BibRef 9800

12.3.4.3 Pose Estimation -- Range Data

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 Abstract. BibRef 9200

Cole, R., Yap, C.K.,
Shape from Probing,
J. 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 Abstract.
WWW Version. 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 Abstract.
WWW Version. BibRef 9408
Earlier: ICCV93(567-571).
IEEE DOI Link 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 Version. 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 Abstract.
WWW Version. 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 Link 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 Link 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 Abstract. 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.
Postscript Version. 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 Version. 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 Abstract.
WWW Version. 0012
BibRef EdinburghFrom 3-D of points of known topology (with noise) BibRef

Wijk, O., Christensen, H.I.,
Triangulation Based Fusion of Sonar Data for Robust Pose Tracking,
RA(16), No. 6, 2000, pp. 740-752.
IEEE Top Reference. BibRef 0001

Greenspan, M.A.[Michael A.],
Geometric Probing of Dense Range Data,
PAMI(24), No. 4, April 2002, pp. 495-508.
IEEE Abstract.
WWW Version. 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

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

Guðmundsson, S.Á.[Sigurjón Árni], Larsen, R.[Rasmus], Ersbøll, B.K.[Bjarne K.],
Robust Pose Estimation Using the SwissRanger SR-3000 Camera,
SCIA07(968-975).
Springer DOI Link 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 Link 0606
BibRef

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

Rui, L., Hirzinger, G.[Gerd],
Marker-Free Automatic Matching Of Range Data,
PanoPhot05(xx-yy).
PDF Version. 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 Link 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).
Postscript Version. 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 Abstract.
WWW Version.
Postscript Version. BibRef 9600

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

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