18.2.6 Optical Flow for Simple Motions

Chapter Contents (Back)
Motion, Translation. Optical Flow, Translation.

Maybank, S.J.,
Algorithm for Analysing Optical Flow Based on the Least-Squares Method,
IVC(4), No. 1, February 1986, pp. 38-42.
Elsevier DOI Moving camera, rigid environment. Irregular surfaces help.
See also Rigid Velocities Compatible with Five Image Velocity Vectors. BibRef 8602

Maybank, S.J.,
The Angular Velocity Associated with the Optical Flowfield Arising from Motion Through a Rigid Environment,
Royal(A-401), 1985, pp. 317-326. BibRef 8500

Maybank, S.J.,
Apparent Area of a Rigid Moving Body,
IVC(5), No. 2, May 1987, pp. 111-113.
Elsevier DOI Change in apparent area, leads to time to contact. BibRef 8705

Maybank, S.J.,
Optical Flow and the Taylor Expansion,
PRL(4), 1986, pp. 243-246. BibRef 8600

Radford, C.J.,
Optical Flow Fields in Hough Transform Space,
PRL(4), 1986, pp. 293-303. BibRef 8600

Emery, W.J., Thomas, A.C., and Collins, M.J.,
An Objective Method for Computing Advective Surface Velocities from Sequential Infrared Images,
JGR(91), No. C11, 1986, pp. 12865-12878. BibRef 8600

Lawton, D.T.[Daryl T.], Gardner, W.F.,
Motion Analysis By Translational Decomposition,
PRL(18), No. 2, February 1997, pp. 203-211. 9704
Translational Decomposition of Flow Fields,
DARPA93(697-705). The flow is represented as local translations. BibRef

Lawton, D.T.[Daryl T.],
Motion Analysis via Local Translational Processing,
CVWS82(59-72). Extract zero crossings, and feature points (corners) then match the corner positions. This generates an optic flow pattern which can give direction of motion for the observer and the scene. BibRef 8200

Lawton, D.T.[Daryl T.],
Processing Dynamic Image Sequences from a Moving Sensor,
Ph.D.Thesis (CS), 1984. BibRef 8400 COINSTR 84-05, UMass. BibRef

Lawton, D.T.[Daryl T.],
Processing Translational Motion Sequences,
CVGIP(22), No. 1, April 1983, pp. 116-144.
Elsevier DOI BibRef 8304
Earlier: COINSTR 82-22, UMass., October 1982. BibRef
Processing Restricted Sensor Motion,
DARPA83(266-281). Generation of some 3-d information for a motion sequence. Procedure to process motion images caused by relative motion of sensor and scene. Feature extraction: pick out small areas which may be distinguishing marks of objects. Search: find the direction of motion which minimizes error. BibRef

Alliney, S.,
Digital Analysis of Rotated Images,
PAMI(15), No. 5, May 1993, pp. 499-504.
IEEE DOI Find relative rotations using image computations and no data interploation. (See also papers that show rotation is independent of center.)
See also Digital Image Registration Using Projections. BibRef 9305

Negahdaripour, S.[Shahriar],
Revised Definition of Optical Flow: Integration of Radiometric and Geometric Cues for Dynamic Scene Analysis,
PAMI(20), No. 9, September 1998, pp. 961-979.
Revised Representation of Optical Flow for Dynamic Scene Analysis,
IEEE DOI University of Miami. Unify geometric interpretation of optical flow and radiometric.
See also BC&GC-Based Dense Stereo By Belief Propagation. BibRef

Negahdaripour, S., Lanjing, J.,
Direct Recovery of Motion and Range from Images of Scenes with Time-Varying Illumination,
IEEE DOI University of Miami. The lighting changes, so the usual models do not apply. BibRef 9500

Negahdaripour, S., and Yu, C.H.,
A Generalized Brightness Change Model for Computing Optical Flow,
IEEE DOI Optical flow computations when the intensity changes from frame to frame. Some experiments with images (2 frames). BibRef 9300

Negahdaripour, S., Yu, C.H.,
Robust Recovery of Motion: Effects of Surface Orientation and Field of View,
IEEE DOI BibRef 8800

Madjidi, H.[Hossein], Negahdaripour, S.[Shahriar],
On robustness and localization accuracy of optical flow computation for underwater color images,
CVIU(104), No. 1, October 2006, pp. 61-76.
Elsevier DOI 0609
On robustness and localization accuracy of optical flow computation from color imagery,
Optical Flow; Color Imagery; Underwater image model BibRef

Gennert, M.A.[Michael A.], and Negahdaripour, S.[Shahriar],
Relaxing the Brightness Constancy Assumption in Computing Optical Flow,
MIT AI Memo-975, June 1987. BibRef 8706

Negahdaripour, S., and Horn, B.K.P.,
Determining 3-D Motion of Planar Objects from Image Brightness Patterns,
IJCAI85(898-901). Translation perpendicular to the surface only. BibRef 8500

Pavlin, I.[Igor], Riseman, E.M., and Hanson, A.R.,
Analysis of an Algorithm for Detection of Translational Motion,
DARPA85(388-398). BibRef 8500
And: COINS-TR-85-47, December 1985. BibRef
And: Camera translation with 8 feature points in 2 images. BibRef

Pavlin, I., Riseman, E.M., and Hanson, A.R.,
A Translational Motion Algorithm Using Hierarchial Search with Smoothing,
No source.
Translational Motion Algorithm with Global Feature Constraints,
COINS-TR-86-58, December 1986. Find the translational motion by recursively reducing the scale in the error surface. This allows for bad initial sampling. BibRef 8612

Tsukune, H., and Aggarwal, J.K.,
Analyzing Orthographic Projection of Multiple 3-D Velocity Vector Fields in Optical Flow,
CVGIP(42), No. 2, May 1988, pp. 157-191.
Elsevier DOI BibRef 8805
Earlier: CVPR85(510-517). (ETL and Univ. of Texas) Motion, Rotation. Hough. Rotational flow and Hough. BibRef

Kanatani, K.I.,
Transformation of Optical Flow by Camera Rotation,
PAMI(10), No. 2, March 1988, pp. 131-143.
IEEE DOI BibRef 8803
Earlier: Motion86(113-118). BibRef
Coordinate Rotation Invariance of Image Characteristics for 3D Shape and Motion Recovery,
ICCV87(55-64). Gunma U. Japan, Now at UMd. Camera rotation effects on Optical Flow of a planar surface that is moving.
See also Camera Rotation Invariance of Image Characteristics. BibRef

Pnueli, Y., Kiryati, N., Bruckstein, A.M.,
Hough Techniques For Fast Optimization of Linear Constant Velocity Motion in Moving Influence Fields,
PRL(15), No. 4, April 1994, pp. 329-336. BibRef 9404

Guan, B.Q.[Bai-Qing], Wang, S.G.[Shi-Gang], Wang, G.B.[Guo-Bao],
A biologically inspired method for estimating 2D high-speed translational motion,
PRL(26), No. 15, November 2005, pp. 2450-2462.
Elsevier DOI 0510

Shih, F.Y.[Frank Y.], Klotz, T.[Tobias], Brockmann, W.[Werner],
A system for rotational velocity computation from image sequences,
IVC(24), No. 4, 1 April 2006, pp. 357-362.
Elsevier DOI Optical flow; Velocity computation; Corner detection; Mathematical morphology 0606

Li, L.[Ling], Yang, Y.Y.[Yong-Yi],
Optical Flow Estimation for a Periodic Image Sequence,
IP(19), No. 1, January 2010, pp. 1-10.
Optical flow estimation for a periodic images sequence,

Taddei, P.[Pierluigi], Espuny, F.[Ferran], Caglioti, V.[Vincenzo],
Planar Motion Estimation and Linear Ground Plane Rectification using an Uncalibrated Generic Camera,
IJCV(96), No. 2, February 2012, pp. 162-174.
WWW Link. 1201
Earlier: A3, A1, Only:
Planar motion estimation using an uncalibrated general camera,
OMNIVIS08(xx-yy). 0810

Hales, I.[Ian], Hogg, D.C.[David C.], Ng, K.[Kia], Boyle, R.[Roger],
Automated Ground-Plane Estimation for Trajectory Rectification,
Springer DOI 1311

Kinoshita, K., Murakami, K.,
Moving object tracking via one-dimensional optical flow using queue,

Kinoshita, K., Enokidani, M., Izumida, M., Murakami, K.,
Tracking of a Moving Object Using One-Dimensional Optical Flow with a Rotating Observer,

Kinoshita, K., Matsushita, H., Izumida, M., Murakami, K.,
Estimation of Inverse Kinematics Model by Forward-Propagation Rule with a High-Order Term,

Porrill, J.[John], Ivins, J.P.[Jim P.], Orban, G.[Guy], Frisby, J.P.[John P.],
The Joint Probability Density Function for Linear Optic Flow Components,
ICPR98(Vol I: 795-798).

Simoncelli, E.P., Adelson, E.H., and Heeger, D.J.,
Probability Distributions of Optical Flow,
PS File. BibRef 9100

Simoncelli, E.P.[Eero P.],
Distributed Analysis and Representation of Visual Motion,
Ph.D.Thesis, MIT. January, 1993.
HTML Version. BibRef 9301
And: (The Tech report listing gives Representation and Analysis, but it is the same document): Vismod209, 1993.
HTML Version. and
PS File. BibRef

Simoncelli, E.P.[Eero P.],
Distributed Representations of Image Velocity,
Vismod202, 1992.
HTML Version. And
PS File. BibRef 9200

Simoncelli, E.P.[Eero P.], Adelson, E.H.[Edward H.],
Computing Optical Flow Distributions Using Spatio-Temporal Filters,
Vismod-165, November 1990, Revised March 1991.
PS File. BibRef 9003

Thomas, I., Simoncelli, E.P., Bajcsy, R.,
Peripheral Visual Field, Fixation and Direction of Heading,
EVAE1995, pp. xx. BibRef 9500

Bobick, A.F.,
Using Stability of Interpretation as Verification for Low Level Processing: An Example from Egomotion and Optic Flow,
IEEE DOI BibRef 9300

Bobick, A.F.[Aaron F.],
A Hybrid Approach to Structure-from-Motion,
Motion83(91-109). (MIT-Psych) Objects are rotated about a fixed axis. BibRef 8300

Roberts, K.S., Bishop, G., Ganapathy, S.K.,
Smooth Interpolation of Rotational Motions,
IEEE DOI BibRef 8800

Diehl, N., Burkhardt, H.,
Planar Motion Estimation with a Fast Converging Algorithm,
ICPR86(1099-1102). BibRef 8600

Chapter on Optical Flow Field Computations and Use continues in
Discontinuous Optic Flow Computation, Occlusions .

Last update:Jul 18, 2024 at 20:50:34