Prazdny, K.,
On the Information in Optical Flows,
CVGIP(22), No. 2, May 1983, pp. 239-259.
WWW Version.
Optical Flow, Evaluation. An evaluation of what can be determined from optical flow. Relative
depth and local surface orientation is possible, but ego motion or
object motion relative to the observer is not directly possible.
BibRef
8305
Williams, T.D.,
Depth from Camera Motion in a Real World Scene,
PAMI(2), No. 6, November 1980, pp. 511-515.
BibRef
8011
And:
Ph.D.Thesis (CS).
Derivation of distance measures for surfaces from optical flow,
restricted to horizontal or vertical surfaces (from static
segmentations). Predicts the image then refines the scene
model.
BibRef
Clocksin, W.F.,
Perception of Surface Slant and Edge Labels from Optical Flow:
A Computational Approach,
Perception(9), 1980, pp. 253-269.
Compute the slant of the surface from the optical flow. The
analysis is for observer translation.
BibRef
8000
Sugihara, K.,
Sugie, N.,
Recovery of Rigid Structure from Orthographically Projected
Optical Flow,
CVGIP(27), No. 3, September 1984, pp. 309-320.
BibRef
8409
Waxman, A.M., and
Ullman, S.,
Surface Structure and Three-Dimensional Motion from
Image Flow Kinematics,
IJRR(4), No. 3, 1985, pp. 72-94.
BibRef
8500
Earlier:
Surface Structure and 3-D Motion from Image Flow: A Kinematic Analysis,
MarylandCAR-TR-24, October 1983.
BibRef
Waxman, A.M.[Allen M.], (UMd),
Kinematics of Image Flows,
DARPA83(175-181).
Generating observer motion from the optic flow pattern.
BibRef
8300
Waxman, A.M.,
Kamgar-Parsi, B., and
Subbarao, M.,
Closed-Form Solutions to Image Flow Equations for
3D Structure and Motion,
IJCV(1), No. 3, October 1987, pp. 239-258.
BibRef
8710
Earlier:
ICCV87(12-24).
Some extensions of the next paper for curved surface patches.
BibRef
Subbarao, M., and
Waxman, A.M.,
Closed Form Solutions to Image Flow Equations for
Planar Surfaces in Motion,
CVGIP(36), No. 2/3, November/December 1986, pp. 208-228.
WWW Version.
BibRef
8611
Earlier:
On the Uniqueness of Image Flow Solutions for Planar Surfaces in Motion,
CVWS85(129-140).
BibRef
And:
MarylandCAR-TR-114, April 1985.
Even more equations, the titles tell it all.
BibRef
Verri, A., and
Poggio, T.A.,
Motion Field and Optical Flow: Qualitative Properties,
PAMI(11), No. 5, May 1989, pp. 490-498.
IEEE Abstract. IEEE Top Reference.
WWW Version.
BibRef
8905
Earlier:
Qualitative Information in the Optical Flow,
DARPA87(825-834). Or:
BibRef
Against Quantitative Optical Flow,
ICCV87(171-180).
BibRef
Earlier:
Motion Field and Optical Flow: Differences and Qualitative Properties,
MIT AI Memo-917, December 1986.
Optical flow is not directly the same as the 3D velocity field.
This derives several properties of the motion field that give
information about the 3-D flow and 3-D structure. Good theory.
BibRef
Kanatani, K.I.,
3-D Interpretation of Optical-Flow by Renormalization,
IJCV(11), No. 3, December 1993, pp. 267-282.
BibRef
9312
Kanatani, K.I.,
Structure and Motion from Optical Flow under Perspective Projection,
CVGIP(38), No. 2, May 1987, pp. 122-146.
Explicit form of the surface from the parameters of the flow. The
same kind of paper as the 1986 on on orthographic projections.
BibRef
8705
Kanatani, K.I.,
Structure and Motion from Optical Flow under Orthographic Projection,
CVGIP(35), No. 2, August 1986, pp. 181-199.
Gunma U. Japan, Then at UMd.
From the flow divide the image into planar regions and determine
their structure and motion. Spurious solutions caused by more than
1 region from the same object. Analytic solutions, no real
results.
See also Tracing Planar Surface Motion from a Projection without Knowing the Correspondence.
BibRef
8608
Mitiche, A.[Amar],
Three-Dimensional Space from Optical Flow Correspondence,
CVGIP(42), No. 3, June 1988, pp. 306-317.
BibRef
8806
Earlier:
Interpretation of Optical Flow Correspondence,
ICPR88(II: 1097-1099).
WWW Version.
IEEE Top Reference. Given the optical flow, compute the relative displacement of the
view points and the position and motion of the points in space. It
uses both OF methods and feature point methods.
BibRef
Mitiche, A.,
Computation of Optical Flow and Rigid Motion,
CVWS84(63-71).
Gradient based approach to optical flow.
BibRef
8400
Mitiche, A.,
Zhuang, X., and
Haralick, R.M.,
Interpretation of Optical Flow by Rotational Decoupling,
CVWS87(195-200).
This tries to relate three different methods by considering optical
flow after removing the rotational component and the standard
thing of recovery of motion and structure from optical flow.
BibRef
8700
Jiang, F., and
Weymouth, T.E.,
Depth from Relative Normal Flows,
PR(23), No. 9, 1990, pp. 1011-1022.
WWW Version.
BibRef
9000
Earlier:
Depth from Dynamic Stereo Images,
CVPR89(250-255).
IEEE Abstract. IEEE Top Reference. Given 2 known camera and a sequence
find the depth. Given a lot of information, simplify the problem.
BibRef
de Micheli, E.,
Giachero, F.,
Motion and Structure from One Dimensional Optical Flow,
CVPR94(962-965).
IEEE Abstract. IEEE Top Reference.
BibRef
9400
Tistarelli, M., and
Sandini, G.,
Dynamic Aspects in Active Vision,
CVGIP(56), No. 1, July 1992, pp. 108-129.
WWW Version.
BibRef
9207
Earlier:
See also Active Dynamic Stereo Vision.
BibRef
Tistarelli, M.[Massimo],
Sandini, G.[Giulio],
Estimation of Depth from Motion Using an Anthropomorphic Visual Sensor,
IVC(8), No. 4, December 1990, pp. 271-278.
BibRef
9012
Earlier:
On the Estimation of Depth from Motion Using an Anthropomorphic
Visual Sensor,
ECCV90(209-225).
WWW Version.
9004
Active Vision.
Depth from Motion.
Log-Polar Sensor.
BibRef
Barron, J.L.,
Jepson, A.D., and
Tsotsos, J.K.,
The Feasibility of Motion and Structure from Noisy Time-Varying
Image Velocity Information,
IJCV(5), No. 3, December 1990, pp. 239-270.
BibRef
9012
Earlier:
The Feasibility Of Motion And Structure Computations,
ICCV88(651-657).
IEEE Abstract. IEEE Top Reference.
BibRef
Earlier:
The Sensitivity of Motion and Structure Computations,
AAAI-87(700-705).
Sensitivity given flow fields, moving observer and
stationary environment.
BibRef
Barron, J.L.,
Jepson, A.D., and
Tsotsos, J.K.,
Determination of Egomotion and Environmental Layout from Noisy
Time-Varying Velocity in Binocular Image Sequences,
IJCAI87(822-825).
BibRef
8700
And:
Determination of Egomotion and Environmental Layout from Noisy
Time-Varying Velocity in Monocular Image Sequences,
CIAP87(XX-YY).
BibRef
MacLean, W.J.,
Jepson, A.D., and
Frecker, R.C.,
Recovery of Ego-Motion and Segmentation of Independent Object Motion
Using the Em Algorithm,
BMVC94(xx).
BibRef
9400
Barron, J.L.,
Motion and Structure in rigid Multi-Surfaced Stationary Environments
Using Time-Varying Image Velocity: Linear Solutions,
VF91(39-46).
Given Optical flow, generate the observer R and T.
BibRef
9100
Barron, J.L.,
Computing Motion and Structure from Noisy,
Time-Varying Image Velocity Information,
RBCV-TR-88-24, Toronto, August 1989,
BibRef
8908
Ph.D.Thesis (CS).
Survey, Motion.
Motion, Survey. It appears that all you would want to know about structure
given optical flow is given here.
BibRef
Murase, H.,
Surface Shape Reconstruction of a Nonrigid
Transparent Object Using Refraction and Motion,
PAMI(14), No. 10, October 1992, pp. 1045-1052.
IEEE Abstract. IEEE Top Reference.
WWW Version.
BibRef
9210
Earlier:
Surface Shape Reconstruction Of An Undulating Transparent Object,
ICCV90(313-317).
WWW Version. Reconstruct the surface of the "water" from the
distortions of the image under it using optical flow.
BibRef
Shu, C.Q.,
Shi, Y.Q.,
On Unified Optical Flow Field,
PR(24), No. 6, 1991, pp. 579-586.
WWW Version.
See also Unified Optical-Flow Field Approach To Motion Analysis from a Sequence of Stereo Images.
BibRef
9100
Shu, C.Q.,
Shi, Y.Q.,
Direct Recovering of Nth Order Surface Structure Using
Unified Optical Flow Field,
PR(26), No. 8, August 1993, pp. 1137-1148.
WWW Version.
BibRef
9308
Shi, Y.Q.,
Shu, C.Q.,
Pan, J.N.,
Unified Optical-Flow Field Approach To Motion Analysis
from a Sequence of Stereo Images,
PR(27), No. 12, December 1994, pp. 1577-1590.
WWW Version.
See also On Unified Optical Flow Field.
BibRef
9412
Pan, J.N.,
Shi, Y.Q.,
Shu, C.Q.,
A Kalman filter in motion analysis from stereo image sequences,
ICIP94(III: 63-67).
WWW Version.
9411
BibRef
Simpson, W.A.,
Optic Flow and Depth Perception,
SV(7), 1993, pp. 35-75.
BibRef
9300
Simpson, W.A.,
The Cross-ratio and the Perception of Motion and Structure,
Motion83(125-129).
(Toronto),
Based on some ideas from Gibson.
BibRef
8300
Gupta, N.C.,
Kanal, L.N.,
3-D Motion Estimation from Motion Field,
AI(78), No. 1-2, October 1995, pp. 45-86.
WWW Version.
BibRef
9510
Gupta, N.C.[Naresh C.],
Kanal, L.N.[Laveen N.],
Gradient Based Image Motion Estimation Without Computing Gradients,
IJCV(22), No. 1, February 1997, pp. 81-101.
WWW Version.
BibRef
9702
Nagle, M.G.,
Srinivasan, M.V.,
Structure-from-Motion:
Determining the Range and Orientation of Surfaces by Image Interpolation,
JOSA-A(13), No. 1, January 1996, pp. 25-34.
BibRef
9601
Mitiche, A.,
Computational Analysis of Visual Motion,
PlenumPress, New York, 1994. ISBN 0-306-44786-X.
3-D interpretation of measured motion from point correspondences,
line correspondences and optical flow, with reduced emphasis on
measuring the motion.
BibRef
9400
Mitiche, A.,
A Computational Approach to the Fusion of Stereopsis and Kineopsis,
MU88(81-99).
BibRef
8800
Earlier:
On Combining Stereopsis And Kineopsis For Space Perception,
CAIA84(156-160).
3-D motion in terms of depth, optical flow and steroscopy parameters.
All this information makes it reasonable (but harder to obtain).
See also On Kineopsis and Computation of Structure and Motion.
BibRef
Lindenbaum, M.,
Bruckstein, A.M.,
Determining Object Shape from Local Velocity Measurements,
PR(21), No. 6, 1988, pp. 591-606.
WWW Version.
BibRef
8800
Raviv, D.,
Albus, J.S.,
A Closed-Form Massively-Parallel Range-from-Image-Flow Algorithm,
SMC(22), 1992, pp. 322-327.
BibRef
9200
Weber, J.[Joseph],
Malik, J.[Jitendra],
Rigid-Body Segmentation and Shape-Description from
Dense Optical-Flow Under Weak Perspective,
PAMI(19), No. 2, February 1997, pp. 139-143.
IEEE Abstract. IEEE Top Reference.
WWW Version.
9703
BibRef
Earlier:
ICCV95(251-256).
WWW Version.
WWW Version. Shape from optical flow. Identify and track independently moving objects
from the optical flow. Rather than discontinuities in the flow field,
use the fact that the epipolar constraint of the individual objects is
different.
BibRef
Allmen, M.C.,
Kegelmeyer, W.P.,
The Computation of Cloud-base Height from Paired Whole-Sky
Imaging Cameras,
MVA(9), No. 4, 1997, pp. 160-165.
HTML Version.
Stereo, Motion.
Optical Flow. Register cloud fields from widely separated cameras. Use optical
flow techniques.
BibRef
9700
Lasenby, J.,
Fitzgerald, W.J.,
Lasenby, A.N.,
Doran, C.J.L.,
New Geometric Methods for Computer Vision:
An Application to Structure and Motion Estimation,
IJCV(26), No. 3, March 1998, pp. 191-213.
WWW Version.
9804
BibRef
Xiong, Y.[Yalin],
Shafer, S.A.[Steven A.],
Dense Structure from a Dense Optical Flow Sequence,
CVIU(69), No. 2, February 1998, pp. 222-245.
WWW Version.
BibRef
9802
Earlier:
SCV95(1-6).
IEEE Top Reference.
BibRef
Earlier:
CMU-RI-TR-95-11, March 1995.
Postscript Version. Carnegie Mellon University.
Reduced complexity to O(N). Only needs 2 frame flow, not long sequence
matching.
BibRef
Xiong, Y.[Yalin],
Shafer, S.A.[Steven A.],
Hypergeometric Filters for Optical Flow and Affine Matching,
IJCV(24), No. 2, September 1997, pp. 163-177.
WWW Version.
9710
BibRef
Earlier:
ICCV95(771-776).
WWW Version.
WWW Version. Formulate these a problems of extracting one of more parameters of a
transformation between images.
BibRef
Xiong, Y.[Yalin],
Shafer, S.A.[Steven A.],
Moment and Hypergeometric Filters for
High Precision Computation of Focus, Stereo and Optical Flow,
IJCV(22), No. 1, February 1997, pp. 25-59.
WWW Version.
BibRef
9702
Earlier:
CMU-RI-TR-94-28, September 1994.
Postscript Version.
BibRef
Xiong, Y.[Yalin],
High Precision Image Matching and Shape Recovery,
CMU-RI-TR-95-35, September 1995.
BibRef
9509
Ph.D.Thesis.
GAbor filters, moment filters, hypergeometric filters. EKF based
structrue from motion.
BibRef
Xiong, Y.,
Shafer, S.A.,
Variable Window Gabor Filters and Their Use in Focus and Correspondence,
CVPR94(668-671).
IEEE Abstract. IEEE Top Reference.
BibRef
9400
And:
CMU-RI-TR-94-06, March 1994.
Postscript Version.
BibRef
And:
Recursive Filters For High Precision Computation of Focus, Stereo
and Optical Flow,
ARPA94(II:1637-1647).
BibRef
Earlier:
Depth from Focusing and Defocusing,
CVPR93(68-73).
IEEE Abstract. IEEE Top Reference.
BibRef
And:
DARPA93(967-).
BibRef
And:
CMU-RI-TR-93-07, March 1993.
Postscript Version.
BibRef
Deshpande, S.G.,
Chaudhuri, S.,
Recursive Estimation of Illuminant Motion from Flow Field
and Simultaneous Recovery of Shape,
CVIU(72), No. 1, October 1998, pp. 10-20.
WWW Version.
BibRef
9810
Earlier:
Recursive estimation of illuminant motion from flow field,
ICIP96(III: 771-774).
WWW Version.
9610
BibRef
Brodský, T.[Tomás],
Fermüller, C.[Cornelia],
Aloimonos, Y.[Yiannis],
Structure from Motion: Beyond the Epipolar Constraint,
IJCV(37), No. 3, June 2000, pp. 231-258.
WWW Version.
0008
BibRef
And:
UMD--TR4000, April 1999.
WWW Version.
WWW Version.
BibRef
Brodský, T.,
Fermüller, C.,
Aloimonos, Y.,
Simultaneous estimation of viewing geometry and structure,
ECCV98(I: 342).
WWW Version.
BibRef
9800
Brodský, T.[Tomás],
Fermüller, C.[Cornelia],
Aloimonos, Y.[Yiannis],
Shape from Video,
CVPR99(II: 146-151).
IEEE Abstract. IEEE Top Reference.
WWW Version. Static scene. First get camera motion, then derive structure.
BibRef
9900
Brodský, T.[Tomás],
Fermüller, C.[Cornelia],
Aloimonos, Y.[Yiannis],
Shape for Video: Beyond the Epipolar Constraint,
DARPA98(1003-1012).
BibRef
9800
Brodský, T.[Tomás],
Fermüller, C.[Cornelia],
Aloimonos, Y.[Yiannis],
Beyond the Epipolar Constraint: Integrating 3D Motion and Structure
Estimation,
SMILE98(xx-yy).
BibRef
9800
Brodsky, T.,
Fermüller, C.,
Aloimonos, Y.,
The Information in the Direction of Image Flow,
SCV95(461-466).
IEEE Top Reference. University of Maryland.
Instead of the full motion field, only use the direction of the flow.
BibRef
9500
Xirouhakis, Y.[Yiannis],
Delopoulos, A.[Anastasios],
Least Squares Estimation of 3D Shape and Motion of Rigid Objects from
Their Orthographic Projections,
PAMI(22), No. 4, April 2000, pp. 393-399.
IEEE Abstract. IEEE Top Reference.
WWW Version.
0006Orthographic projection and flow field.
BibRef
Stein, G.P.[Gideon P.],
Shashua, A.[Amnon],
Model-Based Brightness Constraints:
On Direct Estimation of Structure and Motion,
PAMI(22), No. 9, September 2000, pp. 992-1015.
IEEE Abstract. IEEE Top Reference.
WWW Version.
0010
Extend Horn and Weldon (
See also Direct Methods for Recovering Motion. ) to 3 views
allowing solve for motion and computing dense depth map from spatio-temporal
derivatives.
See also On Degeneracy of Linear Reconstruction From Three Views: Linear Line Complex and Applications.
BibRef
Stein, G.P.[Gideon P.],
Shashua, A.,
Direct Estimation of Motion and Extended Scene Structure
from a Moving Stereo Rig,
CVPR98(211-218).
IEEE Abstract. IEEE Top Reference.
BibRef
9800
Shashua, A.[Amnon],
Wexler, Y.[Yonatan],
Q-Warping: Direct Computation of Quadratic Reference Surfaces,
PAMI(23), No. 8, August 2001, pp. 920-925.
IEEE Abstract. IEEE Top Reference.
WWW Version.
0109
BibRef
Earlier: A2, A1:
CVPR99(I: 333-338).
IEEE Abstract. IEEE Top Reference.
WWW Version.
BibRef
And:
UMD--TR3993, February 1999.
WWW Version.
WWW Version. Analysis based on a picture wrapped around a cylinder. Then apply this
assumption to real data, residual flow is proportional to the 3D of
the surface.
BibRef
Weng, N.,
Yang, Y.H.,
Pierson, R.,
Three-dimensional surface reconstruction using optical flow for medical
imaging,
MedImg(16), No. 5, October 1997, pp. 630-641.
IEEE Top Reference.
0205
BibRef
Muzzolini, R.E.,
Yang, Y.H.[Yee-Hong],
Pierson, R.,
Three dimensional segmentation of volume data,
ICIP94(III: 488-492).
WWW Version.
9411
BibRef
Spies, H.[Hagen],
Jähne, B.[Bernd],
Barron, J.L.[John L.],
Range Flow Estimation,
CVIU(85), No. 3, March 2002, pp. 209-231.
WWW Version.
0211
BibRef
Earlier:
Dense Range Flow from Depth and Intensity Data,
ICPR00(Vol I: 131-134).
WWW Version.
HTML Version.
0009
BibRef
Barron, J.L.[John L.],
Ngai, W.K.J.[Wang Kay Jacky],
Spies, H.[Hagen],
Quantitative Depth Recovery from Time-Varying Optical Flow in a Kalman
Filter Framework,
WTRCV02(346-355).
0204
BibRef
Spies, H.,
Jahne, B.,
Barron, J.L.,
Regularised Range Flow,
ECCV00(II: 785-799).
WWW Version.
0003
BibRef
Spies, H.[Hagen],
Barron, J.L.[John L.],
Estimating Expansion Rates from Range Data Sequences,
VI02(339).
PDF Version.
0208
BibRef
Barron, J.L.[John L.],
Spies, H.[Hagen],
The Fusion of Image and Range Flow,
WTRCV01(171).
0103
BibRef
Liu, H.Y.[Hai-Ying],
Chellappa, R.[Rama],
Rosenfeld, A.[Azriel],
Fast two-frame multiscale dense optical flow estimation using discrete
wavelet filters,
JOSA-A(20), No. 8, August 2003, pp. 1505-1515.
WWW Version.
0308
BibRef
Liu, H.Y.[Hai-Ying],
Chellappa, R.,
Rosenfeld, A.,
Accurate dense optical flow estimation using adaptive structure tensors
and a parametric model,
IP(12), No. 10, October 2003, pp. 1170-1180.
WWW Version.
0310
BibRef
Earlier:
ICPR02(I: 291-294).
WWW Version.
0211
BibRef
Liu, H.Y.[Hai-Ying],
Chellappa, R.,
Rosenfeld, A.,
A hierarchical approach for obtaining structure from two-frame optical
flow,
Motion02(214-219).
IEEE Abstract. IEEE Top Reference.
0303
BibRef
Oliensis, J.[John],
The Least-Squares Error for Structure from Infinitesimal Motion,
IJCV(61), No. 3, February-March 2005, pp. 259-299.
WWW Version.
0412Structure from optical flow.
BibRef
Calway, A.D.[Andrew D.],
Recursive Estimation of 3D Motion and Surface Structure from Local
Affine Flow Parameters,
PAMI(27), No. 4, April 2005, pp. 562-574.
IEEE Abstract. IEEE Top Reference.
0501
BibRef
Earlier:
Estimating the Structure of Textured Surfaces Using Local Affine Flow,
BMVC00(xx-yy).
PDF Version.
0009Optical flow of planar patches on surface.
BibRef
Calway, A.D.,
Kruger, S.,
Tweed, D.,
Motion estimation using adaptive correlation and local directional
smoothing,
ICIP98(III: 614-618).
WWW Version.
9810
BibRef
Kruger, S.,
Calway, A.D.,
Image Registration using Multiresolution Frequency Domain Correlation,
BMVC98(xx-yy).
BibRef
9800
Earlier:
A Multiresolution Frequency Domain Method for
Estimating Affine Motion Parameters,
ICIP96(I: 113-116).
WWW Version.
BibRef
Tan, S.[Sovira],
Dale, J.L.[Jason L.],
Anderson, A.[Andrew],
Johnston, A.[Alan],
Inverse perspective mapping and optic flow:
A calibration method and a quantitative analysis,
IVC(24), No. 2, 1 February 2006, pp. 153-165.
WWW Version.
0604Inverse perspective mapping; Calibration methods
BibRef
Ohnishi, N.[Naoya],
Imiya, A.[Atsushi],
Dominant plane detection from optical flow for robot navigation,
PRL(27), No. 9, July 2006, pp. 1009-1021.
WWW Version. Dominant plane detection; Affine transformation
0605
BibRef
Ohnishi, N.[Naoya],
Imiya, A.[Atsushi],
Visual Navigation of Mobile Robot Using Optical Flow and Visual
Potential Field,
RobVis08(412-426).
WWW Version.
0802
BibRef
Earlier:
Corridor Navigation and Obstacle Avoidance using Visual Potential for
Mobile Robot,
CRV07(131-138).
WWW Version.
0705
BibRef
Ohnishi, N.[Naoya],
Imiya, A.[Atsushi],
Independent Component Analysis of Layer Optical Flow and Its
Application,
BVAI07(171-180).
WWW Version.
0710
BibRef
And:
Model-Based Plane-Segmentation Using Optical Flow and Dominant Plane,
MIRAGE07(295-306).
WWW Version.
0703
BibRef
Imiya, A.[Atsushi],
Yamada, D.[Daisuke],
Voting Method for Stable Range Optical Flow Computation,
PSIVT06(332-341).
WWW Version.
0612
BibRef
Benoit, S.[Stephen],
Ferrie, F.P.[Frank P.],
Towards direct recovery of shape and motion parameters from image
sequences,
CVIU(105), No. 2, February 2007, pp. 145-165.
WWW Version.
0702
BibRef
Earlier:
ICCV03(1395-1402).
WWW Version.
0311Structure from motion; Template matching; Optical flow;
Focus of expansion; Time to collision
Construct filters to recover shape and motion.
BibRef
Lefčvre, J.[Julien],
Baillet, S.[Sylvain],
Optical Flow and Advection on 2-Riemannian Manifolds: A Common
Framework,
PAMI(30), No. 6, June 2008, pp. 1081-1092.
WWW Version.
0804Optical flow for non-planar surfaces.
BibRef
Slesareva, N.[Natalia],
Bruhn, A.[Andrés],
Weickert, J.[Joachim],
Optic Flow Goes Stereo:
A Variational Method for Estimating Discontinuity-Preserving
Dense Disparity Maps,
DAGM05(33).
WWW Version.
0509
BibRef
Zhou, D.X.[Dong-Xiang],
Zhang, H.[Hong],
2D Shape Measurement of Multiple Moving Objects by GMM Background
Modeling and Optical Flow,
ICIAR05(789-795).
WWW Version.
0509
BibRef
Stevens, M.R.,
Snorrason, M.S.,
Eaton, R.S.,
McBride, J.C.,
Motion imagery navigation using terrain estimates,
ICPR04(IV: 272-275).
WWW Version.
0409 See also Single Camera Stereo for Mobile Robot Surveillance.
BibRef
Agarwal, S.[Sameer],
Mallick, S.P.[Satya P.],
Kriegman, D.J.[David J.],
Belongie, S.[Serge],
On Refractive Optical Flow,
ECCV04(Vol II: 483-494).
WWW Version.
0405Recover the refractive structure of an object from a video sequence
acquired as the background behind the refracting object moves.
E.g. a lens.
BibRef
Lopez, J.,
Markel, M.,
Siddiqi, N.,
Gebert, G.,
Performance of passive ranging from image flow,
ICIP03(I: 929-932).
IEEE Abstract. IEEE Top Reference.
0312
BibRef
Wei, T.[Tiangong],
Klette, R.[Reinhard],
Depth Recovery from Noisy Gradient Vector Fields Using Regularization,
CAIP03(116-123).
WWW Version.
0311
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Zucchelli, M.,
Santos-Victor, J.,
Christensen, H.I.,
Maximum likelihood structure and motion estimation integrated over time,
ICPR02(IV: 260-263).
WWW Version.
0211
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ICPR02(I: 339-342).
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ICPR00(Vol I: 881-884).
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HTML Version.
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ECCV00(II: 849-863).
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CVPR00(II: 536-541).
IEEE Abstract. IEEE Top Reference.
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Earlier:
Motion Segmentation and Depth Ordering Based on
Morphological Segmentation,
ECCV98(II: 531).
WWW Version. approximate reconstruction
See also Morphological Segmentation.
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UMDTR3741, February 1997.
WWW Version.
WWW Version. Translating observer characterizes environment by distribution of depths
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ICPR96(I: 528-533).
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9608(Toshiba Kansai Research Lab., J)
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Computing 3D Models of Rotating Objects from Moving Shading,
ICPR96(I: 800-804).
WWW Version.
9608(Kyushu Inst. of Technology, J)
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Direct Estimation of Affine Deformations Using
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ICCV95(134-141).
WWW Version.
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And:
Direct Estimation of Image Deformations Using Visual Front-End Operations
with Automatic Scale Selection,
ISRN KTH/NA/P-94/33-SE, November 1994.
Affine Transform.
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CVPR94(135-140).
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9400
Lawton, D.T.,
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IJCAI81(700-703).
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8100
Earlier:
Constraint-Based Inference from Image Motion,
AAAI-80(31-34).
Uses rigidity to compute Z, then X and Y can be derived.
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Carlsson, S.,
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ECCV94(A:83-91).
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Recursive Estimation of Ego-Motion and Scene Structure
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SCIA91(958-965).
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Carlsson, S.,
Information in the Geometric Structure of Retinal Flow Fields,
ICCV88(629-633).
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See also Passive Navigation.
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8800
Wildes, R.P.,
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AAAI-93(844-850).
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Kersten, D.[Daniel],
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Apparent Opacity Affects Perception of Structure from Motion,
MIT AI Memo-1285, January 1991.
BibRef
9101
Kitahashi, T.[Tadahiro], and
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IJCAI85(902-904).
Vanishing point analysis for motion.
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Loomis, J.M.,
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Motion89(204-211).
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Earlier:
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ICCV88(383-391).
IEEE Abstract. IEEE Top Reference. Psychology, not results.
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Schott, J.P.[Jean-Pierre],
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MIT AI-TR-1162, August 1989.
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Shahraray, B.,
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ICCV88(641-650).
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Pentland, A.P.,
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Motion86(131-136).
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MIT AI Memo-592, December 1980.
BibRef
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Chapter on Optical Flow Field Computations and Use continues in
Real-Time Computation, Hardware for Optical Flow .