17.8 Real-Time Computation, Real-Time Implementation, Hardware for Optical Flow

Chapter Contents (Back)
Implementation. Hardware. Real-Time Optical Flow. See also Parallel Optic Flow Computation, Efficient Computation.

Bulthoff, H.H., Little, J.J., and Poggio, T.A.,
A Parallel Algorithm for Real-time Computation of Optical Flow,
Nature(337), No. 6207, 1989, pp. 549-553. BibRef 8900
And: A2, A1, A3:
A Parallel Motion Algorithm Consistent with Psychophysics and Physiology,
Motion89(165-172). BibRef
And:
Parallel Optical Flow Computation,
DARPA87(915-920). A new algorithm is proposed based on work of Tikhonov that enforces local constraints. This is implemented in parallel on the Connection Machine. BibRef

Little, J.J., Bulthoff, H.H., Poggio, T.,
Parallel Optical Flow Using Local Voting,
ICCV88(454-459).
IEEE DOI BibRef 8800

Bandari, E., and Little, J.J.,
Cooperative analysis of multiple frames by visual echoes,
ICIP94(III: 766-770).
IEEE DOI 9411
BibRef
Earlier:
Visual Echo Analysis,
ICCV93(220-225).
IEEE DOI BibRef
Earlier:
Spatial-Quefrency Approach to Optical Echo Analysis,
CVPR92(850-852).
IEEE DOI Cepstral filtering (Fourier(Fourier X)) applied to optical flow computations. BibRef

Fleet, D.J., Langley, K.,
Recursive Filters For Optical-Flow,
PAMI(17), No. 1, January 1995, pp. 61-67.
IEEE DOI An attempt to get real time computation of optical flow. BibRef 9501

Valentinotti, F., Dicaro, G., Crespi, B.,
Real-Time Parallel Computation of Disparity and Optical-Flow Using Phase Difference,
MVA(9), No. 3, 1996, pp. 87-96.
Springer DOI 9611
BibRef

Smith, S.M.[Stephen M.], Brady, J.M.,
ASSET-2: Real-Time Motion Segmentation and Shape Tracking,
PAMI(17), No. 8, August 1995, pp. 814-820.
IEEE DOI BibRef 9508
And: A1 only: ICCV95(237-244).
IEEE DOI Hardware, real-time tracking of regions of similar flow vectors. Find clusters of flow vectors. In the example, the cluster is constant for a wide range of values. They give a good indication of the effect of the threshold. BibRef

Smith, S.M.,
ASSET-2: Real-Time Motion Segmentation and Object Tracking,
RealTimeImg(4), No. 1, February 1998, pp. 21-40. 9805
BibRef

Smith, S.M.[Stephen M.],
Integrated Real-Time Motion Segmentation and 3D Interpretation,
ICPR96(III: 49-55).
IEEE DOI 9608
BibRef
And: Defence Research AgencyUK, TR96SMS1, 1996. BibRef

Liu, H.C.[Hong-Che], Hong, T.H.[Tsai-Hong], Herman, M.[Martin], Chellappa, R.[Rama],
Motion-Model-Based Boundary Extraction and a Real-Time Implementation,
CVIU(70), No. 1, April 1998, pp. 87-100.
DOI Link BibRef 9804
Earlier:
Motion-Model-Based Boundary Extraction,
SCV95(587-592).
IEEE DOI BibRef
And: UMDTR3414, 1995.
WWW Link. Boundaries within optical flow. See also General Motion Model and Spatiotemporal Filters for Computing Optical-Flow, A. BibRef

Camus, T.A.[Ted A.], Coombs, D.[David], Herman, M.[Martin], Hong, T.H.[Tsai-Hong],
Real-Time Single-Workstation Obstacle Avoidance Using Only Wide-Field Flow Divergence,
Videre(1), No. 3, Summer 1999, pp. xx-yy. BibRef 9900
Earlier: ICPR96(III: 323-330).
IEEE DOI 9608
(National Institute of Standard and Technology, USA) BibRef

Camus, T.A.,
Real-Time Quantized Optical Flow,
RealTimeImg(3), 1997, pp. 71-86. BibRef 9700
Earlier: CAMP95(xx). Implementation of algorithm. Code, Optic Flow.
WWW Link. BibRef

Coombs, D.[David], Herman, M.[Martin], Hong, T.[Tsai], Nashman, M.[Marilyn],
Real-Time Obstacle Avoidance Using Central Flow Divergence and Peripheral Flow,
ICCV95(276-283).
IEEE DOI BibRef 9500
And: NISTIR5605, February 1995.
PS File. And for the report
PS File. BibRef

Herman, M.[Martin], Coombs, D.[David], Hong, T.[Tsai], and Nashman, M.[Marilyn],
Vision-Based Mobility Using Optical Flow,
SPIEInternational Technical Working Group Newsletter, No. 2, Robotics and Machine Perception, Vol. 3, September 1994, pp. 4-5. BibRef 9409

Nishikawa, T.[Tsuyoshi], Tsuboi, Y.[Yoshiro], Takahashi, M.[Masafumi],
System and method for estimating motion vector in macro block,
US_Patent6,031,582, Feb 29, 2000
WWW Link. BibRef 0002

Nishikawa, T.[Tsuyoshi],
System for estimating motion vector with instant estimation of motion vector,
US_Patent6,148,108, Nov 14, 2000
WWW Link. BibRef 0011

Iwamoto, S.[Sadahiro], Checkley, Jr., D.M.[David M.], Trivedi, M.M.[Mohan M.],
REFLICS: Real-time Flow Imaging and Classification System,
MVA(13), No. 1, 2001, pp. 1-13.
Springer DOI Monitoring oceans from real time camera. 0108
BibRef
Earlier: A1, A3, A2: ICPR00(Vol IV: 689-692).
IEEE DOI 0009
BibRef

Björkman, M.[Marten], Eklundh, J.O.[Jan-Olof],
Real-Time Epipolar Geometry Estimation of Binocular Stereo Heads,
PAMI(24), No. 3, March 2002, pp. 425-432.
IEEE DOI 0202
Continuous calibration of external parameters. BibRef

Björkman, M.[Marten], Eklundh, J.O.[Jan-Olof],
A Real-Time System for Epipolar Geometry and Ego-Motion Estimation,
CVPR00(II: 506-513).
IEEE DOI 0005
BibRef

Bjorkman, M., Eklundh, J.O.,
Real-Time Epipolar Geometry Estimation and Disparity,
ICCV99(234-241).
IEEE DOI BibRef 9900

Chong, C.P., Salama, C.A.T., Smith, K.C.,
An imager with built-in image-velocity computation capability,
CirSysVideo(2), No. 3, September 1992, pp. 306-312.
IEEE Top Reference. 0206
BibRef

Chong, C.P., Salama, C.A.T., Smith, K.C.,
A novel technique for image-velocity computation,
CirSysVideo(2), No. 3, September 1992, pp. 313-318.
IEEE Top Reference. 0206
BibRef

Martín, J.L.[José L.], Zuloaga, A.[Aitzol], Cuadrado, C.[Carlos], Lázaro, J.[Jesús], Bidarte, U.[Unai],
Hardware implementation of optical flow constraint equation using FPGAs,
CVIU(98), No. 3, June 2005, pp. 462-490.
WWW Link. 0505
BibRef

Diaz, J.[Javier], Ros, E.[Eduardo], Pelayo, F., Ortigosa, E.M., Mota, S.,
FPGA-based real-time optical-flow system,
CirSysVideo(16), No. 2, February 2006, pp. 274-279.
IEEE DOI 0604
BibRef

Diaz, J.[Javier], Ros, E.[Eduardo], Mota, S., Pelayo, F., Ortigosa, E.M.,
Subpixel motion computing architecture,
VISP(153), No. 6, December 2006, pp. 869-880.
DOI Link 0702
BibRef

Diaz, J.[Javier], Ros, E.[Eduardo], Agis, R.[Rodrigo], Bernier, J.L.[Jose Luis],
Superpipelined high-performance optical-flow computation architecture,
CVIU(112), No. 3, December 2008, pp. 262-273.
WWW Link. 0811
Image motion analysis; Real-time systems; FPGAs; Architecture of vision systems BibRef

Tomasi, M., Vanegas, M., Barranco, F., Diaz, J.[Javier], Ros, E.[Eduardo],
High-Performance Optical-Flow Architecture Based on a Multi-Scale, Multi-Orientation Phase-Based Model,
CirSysVideo(20), No. 12, December 2010, pp. 1797-1807.
IEEE DOI 1102
BibRef

Barranco, F.[Francisco], Tomasi, M.[Matteo], Vanegas, M.[Mauricio], Diaz, J.[Javier], Granados, S.[Sara], Ros, E.[Eduardo],
Hierarchical architecture for motion and depth estimations based on color cues,
RealTimeIP(10), No. 2, June 2015, pp. 435-452.
Springer DOI 1506
BibRef

Tomasi, M., Vanegas, M., Barranco, F., Diaz, J.[Javier], Ros, E.[Eduardo],
Massive Parallel-Hardware Architecture for Multiscale Stereo, Optical Flow and Image-Structure Computation,
CirSysVideo(22), No. 2, February 2012, pp. 282-294.
IEEE DOI 1202
BibRef

Anguita, M., Diaz, J.[Javier], Ros, E.[Eduardo], Fernandez-Baldomero, F.J.,
Optimization Strategies for High-Performance Computing of Optical-Flow in General-Purpose Processors,
CirSysVideo(19), No. 10, October 2009, pp. 1475-1488.
IEEE DOI 0911
BibRef

Ishii, I., Taniguchi, T., Yamamoto, K., Takaki, T.,
High-Frame-Rate Optical Flow System,
CirSysVideo(22), No. 1, January 2012, pp. 105-112.
IEEE DOI 1201
BibRef

Chen, L.[Lei], Takaki, T.[Takeshi], Ishii, I.[Idaku],
Accuracy of Gradient-Based Optical Flow Estimation in High-Frame-Rate Video Analysis,
IEICE(E95-D), No. 4, April 2012, pp. 1130-1141.
WWW Link. 1204
BibRef

Senst, T.[Tobias], Eiselein, V.[Volker], Sikora, T.[Thomas],
Robust Local Optical Flow for Feature Tracking,
CirSysVideo(22), No. 9, September 2012, pp. 1377-1387.
IEEE DOI 1209
BibRef
Earlier:
II-LK: A Real-Time Implementation for Sparse Optical Flow,
ICIAR10(I: 240-249).
Springer DOI 1006
See also Detecting people carrying objects based on an optical flow motion model. BibRef

Senst, T., Geistert, J., Sikora, T.,
Robust local optical flow: Long-range motions and varying illuminations,
ICIP16(4478-4482)
IEEE DOI 1610
Adaptive optics BibRef

Senst, T.[Tobias], Evangelio, R.H.[Ruben Heras], Keller, I.[Ivo], Sikora, T.[Thomas],
Clustering Motion for Real-Time Optical Flow Based Tracking,
AVSS12(410-415).
IEEE DOI 1211
BibRef

Senst, T.[Tobias], Borgmann, T.[Thilo], Keller, I.[Ivo], Sikora, T.[Thomas],
Cross based robust local optical flow,
ICIP14(1967-1971)
IEEE DOI 1502
Accuracy BibRef

Senst, T.[Tobias], Geistert, J.[Jonas], Keller, I.[Ivo], Sikora, T.[Thomas],
Robust local optical flow estimation using bilinear equations for sparse motion estimation,
ICIP13(2499-2503)
IEEE DOI 1402
GPU;KLT;OpenCL;Optical flow;RLOF;feature tracking BibRef

Senst, T.[Tobias], Eiselein, V.[Volker], Evangelio, R.H.[Ruben Heras], Sikora, T.[Thomas],
Robust modified L2 local optical flow estimation and feature tracking,
WMVC11(685-690).
IEEE DOI 1101
BibRef

Senst, T.[Tobias], Eiselein, V.[Volker], Patzold, M.[Michael], Sikora, T.[Thomas],
Efficient real-time local optical flow estimation by means of integral projections,
ICIP11(2345-2348).
IEEE DOI 1201
BibRef

Barranco, F., Díaz, J., Pino, B., Ros, E.,
A multi-resolution approach for massively-parallel hardware-friendly optical flow estimation,
JVCIR(23), No. 8, November 2012, pp. 1272-1283.
Elsevier DOI 1211
Image motion analysis; Optical flow; Field programmable gate array; Architectures for embedded systems; Real-time systems; Multiscale-with-warping optical flow; Efficient multiresolution optical flow; Fusion methods for multiresolution optical flow implementaiton BibRef

Smistad, E.[Erik], Elster, A.C.[Anne C.], Lindseth, F.[Frank],
Real-time gradient vector flow on GPUs using OpenCL,
RealTimeIP(10), No. 1, March 2015, pp. 67-74.
WWW Link. 1503
BibRef

Smistad, E.[Erik], Lindseth, F.[Frank],
Multigrid gradient vector flow computation on the GPU,
RealTimeIP(12), No. 3, October 2016, pp. 593-601.
WWW Link. 1610
BibRef

Plyer, A.[Aurélien], Le Besnerais, G.[Guy], Champagnat, F.[Frédéric],
Massively parallel Lucas Kanade optical flow for real-time video processing applications,
RealTimeIP(11), No. 4, April 2016, pp. 713-730.
Springer DOI 1604
BibRef

Garcia-Rodriguez, J.[Jose], Orts-Escolano, S.[Sergio], Angelopoulou, A.[Anastassia], Psarrou, A.[Alexandra], Azorin-Lopez, J.[Jorge], Garcia-Chamizo, J.M.[Juan Manuel],
Real time motion estimation using a neural architecture implemented on GPUs,
RealTimeIP(11), No. 4, April 2016, pp. 731-749.
Springer DOI 1604
BibRef

Seong, H.S., Rhee, C.E., Lee, H.J.,
A Novel Hardware Architecture of the Lucas-Kanade Optical Flow for Reduced Frame Memory Access,
CirSysVideo(26), No. 6, June 2016, pp. 1187-1199.
IEEE DOI 1606
Adaptive optics See also Iterative Image Registration Technique with an Application to Stereo Vision, An. BibRef


Ridwan, I.[Iffatur], Cheng, H.[Howard],
An Event-Based Optical Flow Algorithm for Dynamic Vision Sensors,
ICIAR17(182-189).
Springer DOI 1706
BibRef

Eilertsen, G.[Gabriel], Forssén, P.E.[Per-Erik], Unger, J.[Jonas],
BriefMatch: Dense Binary Feature Matching for Real-Time Optical Flow Estimation,
SCIA17(I: 221-233).
Springer DOI 1706
BibRef

Smets, S., Goedemé, T., Verhelst, M.,
Custom processor design for efficient, yet flexible Lucas-Kanade optical flow,
DASIP16(138-145)
IEEE DOI 1704
CMOS integrated circuits BibRef

Kroeger, T.[Till], Timofte, R.[Radu], Dai, D.X.[Deng-Xin], Van Gool, L.J.[Luc J.],
Fast Optical Flow Using Dense Inverse Search,
ECCV16(IV: 471-488).
Springer DOI 1611
BibRef

Derome, M.[Maxime], Plyer, A.[Aurelien], Sanfourche, M.[Martial], Le Besnerais, G.[Guy],
A Prediction-Correction Approach for Real-Time Optical Flow Computation Using Stereo,
GCPR16(365-376).
Springer DOI 1611
BibRef

Sundaram, N.[Narayanan], Brox, T.[Thomas], Keutzer, K.[Kurt],
Dense Point Trajectories by GPU-Accelerated Large Displacement Optical Flow,
ECCV10(I: 438-451).
Springer DOI 1009
BibRef

Wei, Z.Y.[Zhao-Yi], Lee, D.J.[Dah-Jye], Nelson, B.E.[Brent E.], Archibald, J.K.[James K.],
Real-time accurate optical flow-based motion sensor,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Pauwels, K.[Karl], Van Hulle, M.M.[Marc M.],
Realtime phase-based optical flow on the GPU,
CVGPU08(1-8).
IEEE DOI 0806
BibRef

Nagy, Y., Saeb, M., El-Sonbaty, Y.,
VHDL-Based Simulation of a Parallel Implementation of a Phase-Based Algorithm for Optical Flow,
AVSBS06(27-27).
IEEE DOI 0611
BibRef

Dopico, A.G.[Antonio G.], Correia, M.V.[Miguel V.], Santos, J.A.[Jorge A.], Nunes, L.M.[Luis M.],
Parallel Computation of Optical Flow,
ICIAR04(II: 397-404).
Springer DOI 0409
BibRef

Correia, M.V.[Miguel V.], Campilho, A.C.[Aurélio C.],
A Pipelined Real-Time Optical Flow Algorithm,
ICIAR04(II: 372-380).
Springer DOI 0409
BibRef
Earlier:
Real-time implementation of an optical flow algorithm,
ICPR02(IV: 247-250).
IEEE DOI 0211
BibRef

Milanova, M.G.[Mariofanna G.], Campilho, A.C.[Aurelio C.], Correia, M.V.[Miguel V.],
Cellular Neural Networks for Motion Estimation,
ICPR00(Vol III: 819-822).
IEEE DOI 0009
BibRef

Adorni, G., Cagnoni, S., Mordonini, M.,
Cellular automata-based optical flow computation for 'just-in-time' applications,
CIAP99(612-617).
IEEE DOI 9909
BibRef

Zuloaga, A., Martin, J.L., Ezquerra, J.,
Hardware architecture for optical flow estimation in real time,
ICIP98(III: 972-976).
IEEE DOI 9810
BibRef

Benoit, S., Ferrie, F.P.,
Monocular Optical Flow for Real-Time Vision Systems,
ICPR96(I: 864-868).
IEEE DOI 9608
(McGill Univ., CDN) BibRef

Bradski, G.R.[Gary R.],
Motion detection using normal optical flow,
US_Patent6,647,131, Nov 11, 2003
WWW Link. BibRef 0311
And: US_Patent6,654,483, Nov 25, 2003
WWW Link. BibRef

Davis, J.W.[James W.], Bradski, G.R.[Gary R.],
Real-time Motion Template Gradients using Intel CVLib,
Frame-Rate99().
HTML Version. BibRef 9900

Nesi, P., del Bimbo, A., and Ben-Tzvi, D.,
Algorithms for Optical Flow Estimation in Real-Time on Connection Machine-2,
Univ. of FlorenceTR, 1993 ??, Systems and Informatics, Faculty of Engineering. Parallel implementation of several optical flow algorithms. Regularization, multiconstraint, M-C with least-squares, M-C with maximum-likelihood. See also Robust Algorithm for Optical-Flow Estimation, A. BibRef 9300

del Bimbo, A., and Nesi, P.,
Optical Flow Estimation on the Connection-Machine CM-2,
CAMP93(267-274). BibRef 9300

del Bimbo, A., and Nesi, P.,
A Vision System for Estimating People Flow,
Univ. of FlorenceTR. 1993 ?? BibRef 9300

Deering, M., Collins, C.,
Real-Time Natural Scene Analysis for a Blind Prosthesis,
IJCAI81(704-709). BibRef 8100


Last update:Aug 9, 2017 at 18:37:22