*Bergholm, F.*, and
*Carlsson, S.*,

**A 'Theory' of Optical Flow**,

*CVGIP(53)*, No. 2, March 1991, pp. 171-188.

Elsevier DOI
BibRef
**9103**

Earlier: A1 only:
*ISRN KTH*/NA/P--88/10--SE, 1988.
BibRef

Earlier:

**Global Structure of Velocity Fields and the
Aperture Problem in the Large**,

*ISRN KTH*/NA/P-87/15-SE, 1987.
Analysis of curves
in motion with normal flow and a few estimates at feature points, produce a
catalog of ambiguous curves and also derive field lines of optical flow.
Theory is appropriate in the title.
BibRef

*Bergholm, F.*,

**Motion from Flow Along Contours:
A Note on Robustness and Ambiguous Cases**,

*IJCV(2)*, No. 4, April 1989, pp. 395-415.

Springer DOI
BibRef
**8904**

And:
`
*ISRN KTH*/NA/P--87/07--SE.
Ambiguous curves: contours without unique motion from normal
velocity. Must use more global information since local information is almost
always ambiguous.
BibRef

*Bergholm, F.*,

**On the Content of Information in Edges and Optical Flow**,

*Ph.D.*Dept. of Numerical Analysis and Computing Science, Royal
Institute of Technology, May 1989.
BibRef
**8905**
*ISRN KTH*/NA/P--89/04--SE.
BibRef

*Bergholm, F.*,

**Decomposition Theory and Transformations of Visual Directions**,

*ICCV90*(85-90).

IEEE DOI
BibRef
**9000**

*Hildreth, E.C.*, (MIT),

**Computing the Velocity Field along Contours**,

*Motion83*(26-32).
BibRef
**8300**

Earlier:

**The Integration of Motion Information along Contours**,

*CVWS82*(83-91).
Requires application of local constraints, since the problem is
inherently ambiguous. The use of the moving contour is important.
Compare to Davis paper.

See also Computation of the Velocity Field, The.
BibRef

*Davis, L.S.[Larry S.]*,
*Wu, Z.Q.[Zhong-Quan]*, and
*Sun, H.F.[Han-Fang]*,

**Contour-Based Motion Estimation**,

*CVGIP(23)*, No. 3, September 1983, pp. 313-326.

Elsevier DOI
BibRef
**8309**

And:
Correction:
*CVGIP(28)*, No. 1, October 1984, pp. 134.
BibRef

Earlier:
*DARPA82*(124-131).
A contour based approach to motion, compute motion at corners, then propagate
along the contours to reach a steady state based on a local 2.5-D motion
assumption. Compare to Hildreth
BibRef

*Faugeras, O.D.*,

**On the Motion of 3D Curves and Its Relationship to Optical Flow**,

*ECCV90*(105-117).

Springer DOI
BibRef
**9000**

And:
*INRIA-Sophia Antipolis*No. 1183, March 1990.
Establish equations given that the curves do not change much.
BibRef

*Faugeras, O.D.*,
*Papadopoulo, T.*,

**A Theory of the Motion Fields of Curves**,

*IJCV(10)*, 1993, pp. 125-156.

Springer DOI

PS File.
BibRef
**9300**

*Papadopoulo, T.[Theo]*,
*Faugeras, O.D.[Olivier D.]*,

**Computing Structure and Motion of General 3D Curves from Monocular
Sequences of Perspective Images**,

*ECCV96*(II:696-708).

Springer DOI
BibRef
**9600**

And:

**Motion Field of Curves: Applications**,

*ECCV94*(A:71-82).

Springer DOI
BibRef

*Wohn, K.[Kwangyoen]*,
*Waxman, A.M.[Allen M.]*,

**The Analytic Structure of Image Flows: Deformation and Segmentation**,

*CVGIP(49)*, No. 2, February 1990, pp. 127-151.

Elsevier DOI From local and global flow structure, determine the analytic boundaries and
thus motion based segmentations. Multiple frame extensions are suggested.

See also Binocular Image Flows: Steps Toward Stereo-Motion Fusion.
BibRef
**9002**

*Waxman, A.M.[Allen M.]*,
*Wohn, K.[Kwangyoen]*,

**Contour Evolution, Neighbourhood Deformation and Global Image Flow:
Planar Surfaces in Motion**,

*IJRR(4)*, 1985, pp. 95-108.
BibRef
**8500**

Earlier:
*UMD-CAR-TR*-58, April, 1984.
Introduces the Taylor series expansion of the motion equations.
BibRef

*Waxman, A.M.[Allen M.]*,
*Wohn, K.[Kwangyoen]*,

**Contour Evolution, Neighborhood Deformation and Image Flow:
Textured Surfaces in Motion**,

*IU87*(72-98).
BibRef
**8700**

*Waxman, A.M.[Allen M.]*,
*Wohn, K.[Kwangyoen]*,

**Image Flow Theory: A Framework for 3-D Inference from
Time-Varying Imagery**,

*ACV88*(I 165-224).
BibRef
**8800**

*Waxman, A.M.[Allen M.]*, (UMd),

**An Image Flow Paradigm**,

*CVWS84*(49-57).
BibRef
**8400**

And:
*RCV87*(145-168).
A general paper to address several issues of what is required for
using optic flow data, and generating
3-D descriptions from the 2-D input data.
BibRef

*Wu, J.[Jian]*, and
*Wohn, K.*,

**On the Deformation of Image Intensity and Zero-Crossing Contours
under Motion**,

*CVGIP(53)*, No. 1, January 1991, pp. 66-75.

Elsevier DOI
BibRef
**9101**

*Waxman, A.M.*,
*Wu, J.*,
*Bergholm, F.*,

**Convected Activation Profiles and the Measurement of Visual Motion**,

*CVPR88*(717-723).

IEEE DOI
BibRef
**8800**

*Waxman, A.M.*, and
*Bergholm, F.*,

**Convected Activation Profiles and Image Flow Extraction**,

*ISRN KTH*/NA/P-87/10-SE, August 1987.
BibRef
**8708**

*Bhanu, B.[Bir]*,
*Burger, W.[Wilhelm]*,

**Approximation of Displacement Fields Using Wavefront Region Growing**,

*CVGIP(41)*, No. 3, March 1988, pp. 306-322.

Elsevier DOI
BibRef
**8803**

And:

**Estimation of Image Motion Using Wavefront Region Growing**,

*ICCV87*(428-432).
BibRef

And:

**System for computing the self-motion of moving images devices**,

*US_Patent*4,969,036, Nov 6, 1990

WWW Link. It might really be motion, but it seems to be contour matching.
Match the contours through a sequence and get the corresponding
points along the contour.
BibRef

*Wu, J.*,
*Brockett, R.*, and
*Wohn, K.*,

**A Contour-Based Recovery of Image Flow: Iterative Transformation Method**,

*PAMI(13)*, No. 8, August 1991, pp. 746-760.

IEEE DOI
BibRef
**9108**

Earlier:

**A Contour-based Recovery of Image Flow: Iterative Method**,

*CVPR89*(124-129).

IEEE DOI Start from the (normal velocity) flow of the contour and smooth it
across the image to get a complete flow field.
BibRef

*Brockett, R.W.*,

**Gramians, Generalized Inverses, and the Least-Squares Approximation of
Optical Flow**,

*JVCIR(1)*, 1990, pp. 3-11.
BibRef
**9000**

*Wohn, K.*, and
*Wu, J.*,

**3-D Motion Recovery from Time-Varying Optical Flows**,

*AAAI-86*(670-675).
BibRef
**8600**

*d'Haeyer, J.P.F.[Johan P.F]*,
*Bruyland, I.[Ignace]*,

**Parallel Computation of Image Curve Velocity Fields**,

*CVGIP(43)*, No. 2, August 1988, pp. 239-255.

Elsevier DOI Parallel solution of a regularization problem.
BibRef
**8808**

*d'Haeyer, J.P.F.[Johan P.F]*,

**Determining Motion of Image Curves from Local Pattern Changes**,

*CVGIP(34)*, No. 2, May 1986, pp. 166-188.

Elsevier DOI (Univ. of Ghent).
The velocity field along a contour is found using a differential
equation. A minimum dilation principle is used to find nonelastic
motion or 2-D rigid motion. Applied to sign language images.
BibRef
**8605**

*Arnspang, J.*,

**On the Use of the Horizon of a Translating Planar Curve**,

*PRL(10)*, 1989, pp. 61-69.
BibRef
**8900**

*Park, J.S.[Jong Seung]*, and
*Han, J.H.[Joon Hee]*,

**Estimating Optical Flow by Tracking Contours**,

*PRL(18)*, No. 7, July 1997, pp. 641-648.
**9711**

BibRef

Earlier:

**A Curvature-Based Approach to Contour Motion Estimation**,

*ICCV98*(1018-1023).

IEEE DOI

See also Contour Matching: A Curvature-Based Approach.
BibRef

*Park, J.S.[Jong Seung]*,
*Han, J.H.[Joon Hee]*,

**Contour Motion Estimation from Image Sequences Using
Curvature Information**,

*PR(31)*, No. 1, January 1998, pp. 31-39.

Elsevier DOI
**9802**

BibRef

*Guerrero, J.J.*,
*Sagues, C.*,

**Camera motion from brightness on lines. Combination of features and
normal flow**,

*PR(32)*, No. 2, February 1999, pp. 203-216.

Elsevier DOI Straight lines and flow for camera motion.
BibRef
**9902**

*Kalmoun, E.[El_Mostafa]*,
*Garrido, L.[Luis]*,
*Caselles, V.[Vicent]*,

**Line Search Multilevel Optimization as Computational Methods for Dense
Optical Flow**,

*SIIMS(4)*, No. 2, 2011, pp. 695-722.

WWW Link.
**1110**

BibRef

*Garrido, L.[Lluís]*,
*Kalmoun, E.[El_Mostafa]*,

**A Line Search Multilevel Truncated Newton Algorithm for Computing the
Optical Flow**,

*IPOL(5)*, 2015, pp. 124-138.

DOI Link
**1508**

*Code, Optical Flow*.
BibRef

*Zheng, J.[Jia]*,
*Wang, H.Y.[Hong-Yan]*,
*Pei, B.N.[Bing-Nan]*,

**Robust optical flow estimation based on wavelet**,

*SIViP(13)*, No. 7, October 2019, pp. 1303-1310.

WWW Link.
**1911**

BibRef

IEEE DOI

Adaptive optics BibRef

*Mahabalagiri, A.[Anvith]*,
*Ozcan, K.[Koray]*,
*Velipasalar, S.[Senem]*,

**Camera motion detection for mobile smart cameras using segmented
edge-based optical flow**,

*AVSS14*(271-276)

IEEE DOI
**1411**

Cameras
BibRef

*Artner, N.M.[Nicole M.]*,
*Kropatsch, W.G.[Walter G.]*,

**Structural Cues in 2D Tracking: Edge Lengths vs. Barycentric
Coordinates**,

*CIARP13*(II:503-511).

Springer DOI
**1311**

BibRef

*Barron, J.L.[John L.]*,
*Daniel, M.*,
*Mari, J.*,

**Using 3D Spline Differentiation to Compute Quantitative Optical Flow**,

*CRV06*(11-11).

IEEE DOI
**0607**

BibRef

*Estépar, R.S.J.[Raúl San José]*,
*Haker, S.[Steve]*,
*Westin, C.F.[Carl-Fredrik]*,

**Riemannian Mean Curvature Flow**,

*ISVC05*(613-620).

Springer DOI
**0512**

BibRef

*Chamorro-Martinez, J.*,
*Fdez-Valdivia, J.*,

**Optical flow estimation based on the extraction of motion patterns**,

*ICIP03*(I: 925-928).

IEEE DOI
**0312**

BibRef

*Neckels, K.[Kai]*,

**Fast Local Estimation of Optical Flow Using Variational and Wavelet
Methods**,

*CAIP01*(349 ff.).

Springer DOI
**0210**

BibRef

*El-Feghali, R.*,
*Mitiche, A.*,

**Fast Computation of a Boundary Preserving Estimate of Optical Flow**,

*BMVC00*(xx-yy).

PDF File.
**0009**

BibRef

*Otsuka, K.*,
*Horikoshi, T.*,
*Suzuki, S.*,

**Image Velocity Estimation from Trajectory Surface in
Spatiotemporal Space**,

*CVPR97*(200-205).

IEEE DOI
**9704**

Spatio-temporal space use edges.
BibRef

*Bergholm, F.*,

**A Theory on Optical Velocity Fields and Ambiguous Motion of Curves**,

*ICCV88*(165-176).

IEEE DOI
BibRef
**8800**

Chapter on Optical Flow Field Computations and Use continues in

Optical Flow Field Computation -- Gradient Techniques .

Last update:May 15, 2022 at 14:39:14