19.3.2 Image Segmentation from Motion Information

DAVIS: Densely Annotated VIdeo Segmentation,
WWW Link.
2017. Dataset, Video Segmentation. For the competition at CVPR 2017.

Video Instance Segmentation - YouTube-VOS,
WWW Link.
Dataset, Video Segmentation. Dataset for video instance segmentation.

Video Instance Segmentation - YouTube-VOS,
WWW Link.
Dataset, Video Segmentation. Dataset for video instance segmentation. And related to Youtube-VIS.

Qi, J.Y.[Ji-Yang], Gao, Y.[Yan], Hu, Y.[Yao], Wang, X.G.[Xing-Gang], Liu, X.Y.[Xiao-Yu], Bai, X.[Xiang], Belongie, S.[Serge], Yuille, A.L.[Alan L.], Torr, P.H.S.[Philip H.S.], Bai, S.[Song],
OVIS: Occluded Video Instance Segmentation,
Online2021. WWW Link.
Dataset, Video Segmentation. Designed with the philosophy of perceiving object occlusions in videos, which could reveal the complexity and the diversity of real-world scenes. BibRef 2100

Potter, J.L.[Jerry L.],
Scene Segmentation Using Motion Information,
CGIP(6), No. 6, December 1977, pp. 558-581.
Elsevier DOI BibRef 7712
Earlier:
Scene Segmentation by Velocity Measurements Obtained with a Cross-Shaped Template,
IJCAI75(803-810). Perform analysis only at grid points. Use a cross template at the grid points. Locate the boundary of the arms of the cross (if any), and use these to follow the object to the next point. Find the match for these templates in next image, T and L templates are introduced to find occluding objects. Nonrigid (continuous) motion, acceleration, z direction motion, and real time analysis is possible. Points are grouped based on velocity (x,y,z), acceleration, and continuity of motion. BibRef

Potter, J.L.,
Velocity as a Cue to Segmentation,
SMC(5), 1975, pp. 390-394. BibRef 7500

Potter, J.L.,
Extraction and Utilization of Motion in Scene Description,
Ph.D.Univ. of Wisconsin, 1974. BibRef 7400

Murray, D.W., and Buxton, B.F.,
Scene Segmentation from Visual Motion Using Global Optimization,
PAMI(9), No. 2, March 1987, pp. 220-228. Uses a MAP criterion and simulated annealing to search for the optimal segmentation when given the optical flow. 1200 iterations are used. BibRef 8703

Murray, D.W., and Buxton, B.F.,
Experiments in the Machine Interpretation of Visual Motion,
Cambridge: MIT Press1990. BibRef 9000 BookAlgorithms and systems for 2-D motion in an image, the 3-D structure and object recognition. BibRef

Harris, J.G.,
An Analog Network for Continuous-Time Segmentation,
IJCV(10), No. 1, February 1993, pp. 43-51.
Springer DOI Hardware implementation of motion segmentation technique.
See also Analog Hardware for Detecting Discontinuities in Early Vision. BibRef 9302

Park, D.,
Adaptive Bayesian Decision-Model for Motion Segmentation,
PRL(15), No. 12, December 1994, pp. 1183-1189. BibRef 9412

Tanaka, M.,
On the Representation of the Projected Motion Group in 2+1D,
PRL(14), 1993, pp. 871-678. BibRef 9300

Tanaka, M., Kurita, T., Umeyama, S.,
Image Understanding Via Representation of the Projected Motion Group,
PRL(15), No. 10, October 1994, pp. 993-1001. BibRef 9410

Zheng, H.Y., Blostein, S.D.,
Motion-Based Object Segmentation and Estimation Using the MDL Principle,
IP(4), No. 9, September 1995, pp. 1223-1235.
IEEE DOI BibRef 9509

Choi, J.G., Lee, S.W., Kim, S.D.,
Spatiotemporal Video Segmentation Using a Joint Similarity Measure,
CirSysVideo(7), No. 2, April 1997, pp. 279-286.
IEEE Top Reference. 9704
BibRef

Lee, S.W., Choi, J.G., Kim, S.D.,
Scene Segmentation Using a Combined Criterion of Motion and Intensity,
OptEng(36), No. 8, August 1997, pp. 2346-2352. 9708
BibRef

Borshukov, G.D., Bozdagi, G., Altunbasak, Y., Tekalp, A.M.,
Motion Segmentation by Multistage Affine Classification,
IP(6), No. 11, November 1997, pp. 1591-1594.
IEEE DOI 9710
Build on Wang and Adelson:
See also Representing Moving Images with Layers. Clustering replaced by merging, implement in multiple stages. BibRef

Bober, M.[Miroslaw], Petrou, M., Kittler, J.V.,
Nonlinear Motion Estimation Using The Supercoupling Approach,
PAMI(20), No. 5, May 1998, pp. 550-555.
IEEE DOI 9806
BibRef
Earlier: A2, A1, A3:
Multiresolution Motion Segmentation,
ICPR94(A:379-383). Efficient multiresolution approach for motion segmentation. BibRef

Zhang, K.[Kui], Bober, M., Kittler, J.V.,
Video Coding Using Affine Motion Compensated Prediction,
ICASSP96(XX). BibRef 9600
And:
Motion Based Image Segmentation for Video Coding,
ICIP95(III: 476-479).
IEEE DOI 9510
BibRef
And:
Motion Compensation: The Selection of Optimal Motion Estimation Technique and Quantization Levels,
DSP95(457-462). BibRef
And:
Variable Block Size Video Coding with Motion Prediction and Motion Segmentation,
SPIE(2419), February 1995, pp. 62-70. BibRef
And:
Robust Motion Estimation and Multistage VQ for Sequence Compression,
ICIP94(II: 452-456).
IEEE DOI 9411
Dept. of Electronic Eng.. University of Surrey. BibRef

Salari, E., Li, W.,
A fast quadtree motion segmentation for image sequence coding,
SP:IC(14), No. 10, August 1999, pp. 811-816.
Elsevier DOI BibRef 9908

Vasconcelos, N.M.[Nuno M.], Lippman, A.[Andrew],
Empirical Bayesian Motion Segmentation,
PAMI(23), No. 2, February 2001, pp. 217-221.
IEEE DOI 0102
BibRef
Earlier:
Empirical Bayesian EM Based Motion Segmentation,
CVPR97(527-532).
IEEE DOI 9704
(other paper?) Expectation maximation (motion with occlusions) Layered motion representation.
See also Statistical Models of Video Structure for Content Analysis and Characterization. BibRef

Wiskott, L.[Laurenz],
Segmentation from motion: Combining Gabor- and Mallat-Wavelets to Overcome the Aperture and Correspondence Problems,
PR(32), No. 10, October 1999, pp. 1751-1766.
Elsevier DOI BibRef 9910
Earlier:
Segmentation from Motion: Combining Gabor- and Mallat-Wavelets to Overcome Aperture and Correspondence Problem,
CAIP97(329-336).
Springer DOI 9709
BibRef
And: TR-IR-INI 96-10, Institut fur Neuroinformatik, Ruhr-Universitat Bochum, 44780 Bochum, Germany, November 1996.
HTML Version. and
PS File. BibRef

Kim, J.S.[Jin-Sang], Chen, T.[Tom],
Multiple feature clustering for image sequence segmentation,
PRL(22), No. 11, September 2001, pp. 1207-1217.
Elsevier DOI 0108
BibRef
Earlier:
Segmentation of Image Sequences Using SOFM Networks,
ICPR00(Vol III: 869-872).
IEEE DOI 0009
BibRef

Rodríguez, J.A., Urdiales García, C.[Cristina], Bandera Rubio, A.[Antonio], Sandoval Hernández, F.[Francisco],
Nonuniform video coding by means of multifoveal geometries,
IJIST(12), No. 1, 2002, pp. 27-34.
WWW Link. 0202
BibRef

Rodríguez, J.A., Urdiales García, C.[Cristina], Bandera Rubio, A.[Antonio], Sandoval Hernández, F.[Francisco],
A multiresolution spatiotemporal motion segmentation technique for video sequences based on pyramidal structures,
PRL(23), No. 14, December 2002, pp. 1761-1769.
Elsevier DOI 0208
BibRef

Valencia, G., Rodríguez, J.A., Urdiales García, C.[Cristina], Bandera Rubio, A.[Antonio], Sandoval Hernández, F.[Francisco],
Spatiotemporal video segmentation and motion estimation through irregular pyramids,
PR(36), No. 6, June 2003, pp. 1445-1447.
Elsevier DOI 0304
BibRef

Valencia, G., Rodríguez, J.A., Urdiales García, C.[Cristina], Sandoval Hernández, F.[Francisco],
Color-based video segmentation using interlinked irregular pyramids,
PR(37), No. 2, February 2004, pp. 377-380.
Elsevier DOI 0311
BibRef

Sifakis, E.[Eftychis], Grinias, I.[Ilias], Tziritas, G.[Georgios],
Video Segmentation Using Fast Marching and Region Growing Algorithms,
JASP(2002), No. 4, 2002, pp. 379-388.
WWW Link. 0204

See also Colour and Texture Segmentation Using Wavelet Frame Analysis, Deterministic Relaxation, and Fast Marching Algorithms. BibRef

Grinias, I., Tziritas, G.,
A semi-automatic seeded region growing algorithm for video object localization and tracking,
SP:IC(16), No. 10, August 2001, pp. 977-986.
Elsevier DOI 0001
BibRef

Panagiotakis, C., Grinias, I., Tziritas, G.,
Natural Image Segmentation Based on Tree Equipartition, Bayesian Flooding and Region Merging,
IP(20), No. 8, August 2011, pp. 2276-2287.
IEEE DOI 1108
BibRef

Grinias, I., Tziritas, G.,
Foreground object localization using a flooding algorithm based on inter-frame change and colour,
AVSBS07(523-527).
IEEE DOI 0709
BibRef

Sifakis, E.[Eftychis], Tziritas, G.[Georgios],
Moving object localisation using a multi-label fast marching algorithm,
SP:IC(16), No. 10, August 2001, pp. 963-976.
Elsevier DOI 0001
BibRef
Earlier:
Fast Marching to Moving Object Location,
ScaleSpace99(447-452). Change detection, Video object segmentation, Fast marching algorithm BibRef

Mansouri, A.R.[Abdol-Reza], Konrad, J.[Janusz],
Multiple Motion Segmentation with Level Sets,
IP(12), No. 2, February 2003, pp. 201-220.
IEEE DOI 0304
BibRef
Earlier:
Motion Segmentation with Level Sets,
ICIP99(II:126-130).
IEEE DOI
See also Approximation of Images by Basis Functions for Multiple Region Segmentation with Level Sets. BibRef

Fowlkes, C.C.[Charless C.], Belongie, S.J.[Serge J.], Chung, F.[Fan], Malik, J.[Jitendra],
Spectral Grouping Using the Nystrom Method,
PAMI(26), No. 2, February 2004, pp. 214-225.
IEEE Abstract. 0402
BibRef
Earlier: A2, A1, A3, A4:
Spectral Partitioning with Indefinite Kernels Using the Nyström Extension,
ECCV02(III: 531 ff.).
Springer DOI 0205

See also Normalized Cuts and Image Segmentation.
See also Efficient Spatiotemporal Grouping Using the Nyström Method. Reduce computation time so that algorithm can be applied in motion application. Leverage the fact that there are more pixels than coherent groups. BibRef

Fowlkes, C.C., Belongie, S.J., Malik, J.,
Efficient Spatiotemporal Grouping Using the Nyström Method,
CVPR01(I:231-238).
IEEE DOI 0110

See also Normalized Cuts and Image Segmentation. Motion segmentation, Spectral segmentation then motion. BibRef

Tripathi, S.[Subarna], Belongie, S.J.[Serge J.], Hwang, Y.[Youngbae], Nguyen, T.[Truong],
Detecting temporally consistent objects in videos through object class label propagation,
WACV16(1-9)
IEEE DOI 1606
BibRef
Earlier: A1, A3, A2, A4:
Improving streaming video segmentation with early and mid-level visual processing,
WACV14(477-484)
IEEE DOI 1406
Accuracy BibRef

Calderón, F.[Felix], Marroquín, J.L.[Jose L.], Botello, S.[Salvador], Vemuri, B.C.[Baba C.],
The MPM-MAP algorithm for motion segmentation,
CVIU(95), No. 2, August 2004, pp. 165-183.
Elsevier DOI 0409
BibRef
Earlier: A2, A3, A1, A4:
The MPM-MAP Algorithm for Image Segmentation,
ICPR00(Vol I: 303-308).
IEEE DOI 0009

See also Hidden Markov measure field models for image segmentation. BibRef

Kim, E.Y.[Eun Yi], Hwang, S.W.[Sang Won], Park, S.H.[Se Hyun], Kim, H.J.[Hang Joon],
Spatiotemporal segmentation using genetic algorithms,
PR(34), No. 10, October 2001, pp. 2063-2066.
Elsevier DOI 0108
BibRef

Kim, E.Y.[Eun Yi], Park, S.H.[Se Hyun], Hwang, S.W.[Sang Won], Kim, H.J.[Hang Joon],
Video sequence segmentation using genetic algorithms,
PRL(23), No. 7, May 2002, pp. 843-863.
Elsevier DOI 0203
BibRef
Earlier: A3, A1, A2, A4:
Object Extraction and Tracking Using Genetic Algorithms,
ICIP01(II: 383-386).
IEEE DOI 0108
BibRef

Kim, E.Y.[Eun Yi], Park, S.H.[Se Hyun],
Automatic video segmentation using genetic algorithms,
PRL(27), No. 11, August 2006, pp. 1252-1265.
Elsevier DOI 0606
BibRef
Earlier:
A Genetic Algorithm with Automatic Parameter Adaptation for Video Segmentation,
CAIP03(238-245).
Springer DOI 0311
Genetic algorithm, Markov random fields, Object detection, Tracking BibRef

Park, S.H.[Se Hyun], Kim, E.Y.[Eun Yi], Cho, B.J.[Beom-Joon],
Genetic Algorithm-Based Video Segmentation with Adaptive Population Size,
DAGM03(426-433).
Springer DOI 0310
BibRef

Kim, E.Y.[Eun Yi], Jung, K.C.[Kee-Chul],
Genetic algorithms for video segmentation,
PR(38), No. 1, January 2005, pp. 59-73.
Elsevier DOI 0410
BibRef

Ayvaci, A.[Alper], Raptis, M.[Michalis], Soatto, S.[Stefano],
Sparse Occlusion Detection with Optical Flow,
IJCV(97), No. 3, May 2012, pp. 322-338.
WWW Link. 1203
Lambertian reflection and static illumination. A variational optimization problem.
See also Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation. BibRef

Georgiadis, G.[Georgios], Ayvaci, A.[Alper], Soatto, S.[Stefano],
Actionable saliency detection: Independent motion detection without independent motion estimation,
CVPR12(646-653).
IEEE DOI 1208
BibRef

Ayvaci, A.[Alper], Soatto, S.[Stefano],
Detachable Object Detection: Segmentation and Depth Ordering from Short-Baseline Video,
PAMI(34), No. 10, October 2012, pp. 1942-1951.
IEEE DOI 1208
BibRef
Earlier:
Detachable Object Detection with Efficient Model Selection,
EMMCVPR11(191-204).
Springer DOI 1107
BibRef
Earlier:
Motion segmentation with occlusions on the superpixel graph,
WDV09(727-734).
IEEE DOI 0910
Appearance and motion. BibRef

Lauer, F.[Fabien], Schnorr, C.[Christoph],
Spectral clustering of linear subspaces for motion segmentation,
ICCV09(678-685).
IEEE DOI 0909
BibRef

Cremers, D.[Daniel], Yuille, A.L.[Alan L.],
A Generative Model Based Approach to Motion Segmentation,
DAGM03(313-320).
Springer DOI 0310
BibRef

Nordberg, K.[Klas], Farnebäck, G.[Gunnar],
Estimation of orientation tensors for simple signals by means of second-order filters,
SP:IC(20), No. 6, July 2005, pp. 582-594.
Elsevier DOI 0506
BibRef
Earlier:
A framework for estimation of orientation and velocity,
ICIP03(III: 57-60).
IEEE DOI 0312
BibRef

Farnebäck, G.[Gunnar],
Polynomial Expansion for Orientation and Motion Estimation,
Ph.D.Thesis, Linkoping University, 2002.
HTML Version. BibRef 0200

Farnebäck, G.[Gunnar],
Two-Frame Motion Estimation Based on Polynomial Expansion,
SCIA03(363-370).
Springer DOI 0310
BibRef

Farnebäck, G.[Gunnar],
Very High Accuracy Velocity Estimation using Orientation Tensors, Parametric Motion, and Simultaneous Segmentation of the Motion Field,
ICCV01(I: 171-177).
IEEE DOI 0106
BibRef
Earlier:
Fast and Accurate Motion Estimation Using Orientation Tensors and Parametric Motion Models,
ICPR00(Vol I: 135-139).
IEEE DOI 0009
BibRef

Farnebäck, G.[Gunnar],
Motion-Based Segmentation of Image Sequences Using Orientation Tensors,
SSAB97(Computer Vision) 9703
BibRef

Fan, Z.M.[Zhi-Min], Zhou, J.[Jie], Wu, Y.[Ying],
Multibody Grouping by Inference of Multiple Subspaces from High-Dimensional Data Using Oriented-Frames,
PAMI(28), No. 1, January 2006, pp. 91-105.
IEEE DOI 0512
BibRef
Earlier:
Inference of multiple subspaces from high-dimensional data and application to multibody grouping,
CVPR04(II: 661-666).
IEEE DOI 0408
BibRef
And:
Multibody motion segmentation based on simulated annealing,
CVPR04(I: 776-781).
IEEE DOI 0408
BibRef

Wong, K.Y.[King Yuen], Spetsakis, M.E.[Minas E.],
Tracking based motion segmentation under relaxed statistical assumptions,
CVIU(101), No. 1, January 2005, pp. 45-64.
Elsevier DOI 0512
BibRef
Earlier:
Motion Segmentation by EM Clustering of Good Features,
VideoRegister04(166).
WWW Link. 0502
BibRef
Earlier:
Motion Segmentation and Tracking,
VI02(80).
PDF File. 0208
BibRef

Wong, K.Y., Ye, L., Spetsakis, M.E.,
EM Clustering of Incomplete Data Applied to Motion Segmentation,
BMVC04(xx-yy).
HTML Version. 0508
BibRef

Bicego, M.[Manuele], Cristani, M.[Marco], Murino, V.[Vittorio],
Unsupervised scene analysis: A hidden Markov model approach,
CVIU(102), No. 1, April 2006, pp. 22-41.
Elsevier DOI 0604
Scene analysis, Video processing, Video segmentation, Scene understanding, Video surveillance
See also Similarity-Based Classification of Sequences Using Hidden Markov Models. BibRef

Regazzoni, C.S., Murino, V.[Vittorio],
Multilevel GMRF-based segmentation of image sequences,
ICPR92(II:713-716).
IEEE DOI 9208
BibRef

Vazquez, C., Mitiche, A., Laganiere, R.,
Joint Multiregion Segmentation and Parametric Estimation of Image Motion by Basis Function Representation and Level Set Evolution,
PAMI(28), No. 5, May 2006, pp. 782-793.
IEEE DOI 0604
BibRef

Gheissari, N.[Niloofar], Bab-Hadiashar, A.[Alireza], Suter, D.[David],
Parametric model-based motion segmentation using surface selection criterion,
CVIU(102), No. 2, May 2006, pp. 214-226.
Elsevier DOI 0605
BibRef
Earlier: A2, A1, A3:
Robust model based motion segmentation,
ICPR02(II: 753-756).
IEEE DOI 0211
Model selection, Optic flow, Motion estimation
See also Robust Optic Flow Computation. BibRef

Bab-Hadiashar, A.[Alireza], Gheissari, N.[Niloofar],
Range Image Segmentation Using Surface Selection Criterion,
IP(15), No. 7, July 2006, pp. 2006-2018.
IEEE DOI 0606
BibRef

Gheissari, N.[Niloofar], Bab-Hadiashar, A.[Alireza],
Motion analysis: Model selection and motion segmentation,
CIAP03(442-448).
IEEE DOI 0310

See also Model Selection for Range Segmentation of Curved Objects. BibRef

Bab-Hadiashar, A.[Alireza],
Range and Motion Segmentation: A Robust Approach,
TRMonash University. 1998.
PS File. BibRef 9800

Bab-Hadiashar, A.[Alireza], Suter, D.[David],
Robust Range Segmentation,
ICPR98(Vol II: 969-971).
IEEE DOI 9808

See also Robust Optic Flow Computation. BibRef

Li, H.L.[Hong-Liang], Ngan, K.N.[King Ngi],
Unsupervized Video Segmentation With Low Depth of Field,
CirSysVideo(17), No. 12, December 2007, pp. 1742-1751.
IEEE DOI 0712
BibRef
Earlier:
Unsupervised Segmentation of Defocused Video Based on Matting Model,
ICIP06(1825-1828).
IEEE DOI 0610
BibRef

Li, H.L.[Hong-Liang], Ngan, K.N.[King Ngi], (Eds.)
Video Segmentation and Its Applications,
Springer2011, ISBN: 978-1-4419-9481-3
WWW Link. Buy this book: Video Segmentation and Its Applications 1106
Gestures and other signals. BibRef

Ronse, C.[Christian], Agnus, V.[Vincent],
Geodesy on label images, and applications to video sequence processing,
JVCIR(19), No. 6, August 2008, pp. 392-408.
Elsevier DOI 0804
Label images, Mathematical morphology, Geodesic (conditional) dilation and erosion, Geodesic reconstruction, Non-distributive lattice; Complete lattice, Connectivity BibRef

Agnus, V.[Vincent], Ronse, C.[Christian], Heitz, F.[Fabrice],
Spatio-temporal Segmentation Using 3d Morphological Tools,
ICPR00(Vol III: 877-880).
IEEE DOI 0009
BibRef

Conaire, C.Ó.[Ciarán Ó.], O'Connor, N.E.[Noel E.], Smeaton, A.F.[Alan F.],
Thermo-visual feature fusion for object tracking using multiple spatiogram trackers,
MVA(19), No. 5-6, October 2008, pp. xx-yy.
Springer DOI 0810
BibRef

Conaire, C.O., O'Connor, N.E., Cooke, E., Smeaton, A.F.,
Multispectral Object Segmentation and Retrieval in Surveillance Video,
ICIP06(2381-2384).
IEEE DOI 0610
BibRef

Montoliu, R.[Raúl], Pla, F.[Filiberto],
Generalized least squares-based parametric motion estimation,
CVIU(113), No. 7, July 2009, pp. 790-801.
Elsevier DOI 0905
BibRef
Earlier:
Generalized Least Squares-Based Parametric Motion Estimation Under Non-uniform Illumination Changes,
ICIAR08(xx-yy).
Springer DOI 0806
BibRef
Earlier:
Multiple Parametric Motion Model Estimation and Segmentation,
ICIP01(II: 933-936).
IEEE DOI 0108
Image Registration, Robust estimation, Outlier detection, Motion estimation, Generalized least squares estimation BibRef

Ryan, K., Amer, A., Gagnon, L.,
Spatiotemporal Region Enhancement and Merging for Unsupervized Object Segmentation,
JIVP(2009), No. 2009, pp. xx-yy.
DOI Link 0909
Offline video segmentation. Initial color and motion variance, then motion tracking through the sequence. BibRef

Wen, C.L.[Chung-Lin], Chen, B.Y.[Bing-Yu], Sato, Y.[Yoichi],
Video Segmentation with Motion Smoothness,
IEICE(E93-D), No. 4, April 2010, pp. 873-881.
WWW Link. 1003
graph-cut-based. Color and motion both. BibRef

Lu, X.Y.[Xiao-Ye], Manduchi, R.[Roberto],
Fast image motion segmentation for surveillance applications,
IVC(29), No. 2-3, February 2011, pp. 104-116.
Elsevier DOI 1101
Optical flow, Motion computation, Belief propagation BibRef

Gai, K.[Kun], Shi, Z.W.[Zhen-Wei], Zhang, C.S.[Chang-Shui],
Blind Separation of Superimposed Moving Images Using Image Statistics,
PAMI(34), No. 1, January 2012, pp. 19-32.
IEEE DOI 1112
BibRef
Earlier:
Blind separation of superimposed images with unknown motions,
CVPR09(1881-1888).
IEEE DOI 0906
BibRef
Earlier:
Blindly separating mixtures of multiple layers with spatial shifts,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Wu, S.[Si], Wong, H.S.[Hau San],
Joint segmentation of collectively moving objects using a bag-of-words model and level set evolution,
PR(45), No. 9, September 2012, pp. 3389-3401.
Elsevier DOI 1206
Collective motion, Segmentation, Bag-of-words, Level set BibRef

Nedrich, M.[Matthew], Davis, J.W.[James W.],
Detecting behavioral zones in local and global camera views,
MVA(24), No. 3, April 2013, pp. 579-605.
WWW Link. 1303
BibRef
Earlier:
Learning Scene Entries and Exits Using Coherent Motion Regions,
ISVC10(I: 120-131).
Springer DOI 1011
BibRef

Dimitriou, N.[Nikolaos], Delopoulos, A.[Anastasios],
Motion-based segmentation of objects using overlapping temporal windows,
IVC(31), No. 9, 2013, pp. 593-602.
Elsevier DOI 1307
BibRef
And:
Motion segmentation via overlapping temporal windows,
ICIP13(4239-4243)
IEEE DOI 1402
BibRef
Earlier:
Improved motion segmentation using Locally sampled Subspaces,
ICIP12(309-312).
IEEE DOI 1302
affine model. Motion segmentation BibRef

Dimitriou, N.[Nikolaos], Delopoulos, A.[Anastasios],
Incorporating higher order models for occlusion resilient motion segmentation in streaming videos,
IVC(36), No. 1, 2015, pp. 70-82.
Elsevier DOI 1504
BibRef
Earlier:
Fast, robust and occlusion resilient motion based video segmentation,
ICIP14(4398-4402)
IEEE DOI 1502
Motion segmentation BibRef

Wan, P., Feng, Y., Cheung, G., Bajic, I.V., Au, O.C.,
3-D Motion Estimation for Visual Saliency Modeling,
SPLetters(20), No. 10, 2013, pp. 972-975.
IEEE DOI 1309
Cameras BibRef

Juliet, S.E.[S. Ebenezer], Sadasivam, V., Florinabel, D.J.[D. Jemi],
Effective layer-based segmentation of compound images using morphology,
RealTimeIP(9), No. 2, June 2014, pp. 299-314.
Springer DOI 1407
BibRef

Gao, Z.[Zhi], Cheong, L.F.[Loong-Fah], Wang, Y.X.[Yu-Xiang],
Block-Sparse RPCA for Salient Motion Detection,
PAMI(36), No. 10, October 2014, pp. 1975-1987.
IEEE DOI 1410
image motion analysis BibRef

Gao, Z.[Zhi], Cheong, L.F.[Loong-Fah], Shan, M.[Mo],
Block-Sparse RPCA for Consistent Foreground Detection,
ECCV12(V: 690-703).
Springer DOI 1210
BibRef

Guo, J.[Jia_Ming], Cheong, L.F.[Loong-Fah], Tan, R.T.[Robby T.], Zhou, S.Z.Y.[Steven Zhi-Ying],
Consistent Foreground Co-segmentation,
ACCV14(IV: 241-257).
Springer DOI 1504
BibRef

Guo, J.M.[Jia-Ming], Li, Z.W.[Zhu-Wen], Cheong, L.F.[Loong-Fah], Zhou, S.Z.Y.[Steven Zhi-Ying],
Video Co-segmentation for Meaningful Action Extraction,
ICCV13(2232-2239)
IEEE DOI 1403
BibRef

Li, Z.W.[Zhu-Wen], Guo, J.M.[Jia-Ming], Cheong, L.F.[Loong-Fah], Zhou, S.Z.Y.[Steven Zhi-Ying],
Perspective Motion Segmentation via Collaborative Clustering,
ICCV13(1369-1376)
IEEE DOI 1403
BibRef

Lee, C.M.[Choon-Meng], Cheong, L.F.[Loong-Fah],
Minimal Basis Subspace Representation: A Unified Framework for Rigid and Non-rigid Motion Segmentation,
IJCV(121), No. 2, January 2017, pp. 209-233.
Springer DOI 1702
BibRef
Earlier:
Minimal Basis Facility Location for Subspace Segmentation,
ICCV13(1585-1592)
IEEE DOI 1403
Hopkins 155 BibRef

Jiang, H.Q.[Han-Qing], Zhang, G.F.[Guo-Feng], Wang, H.Y.[Hui-Yan], Bao, H.J.[Hu-Jun],
Spatio-Temporal Video Segmentation of Static Scenes and Its Applications,
MultMed(17), No. 1, January 2015, pp. 3-15.
IEEE DOI 1502
image colour analysis BibRef

Kannan, R.[Rajkumar], Ghinea, G.[Gheorghita], Swaminathan, S.[Sridhar],
Discovering salient objects from videos using spatiotemporal salient region detection,
SP:IC(36), No. 1, 2015, pp. 154-178.
Elsevier DOI 1509
Salient region detection BibRef

Wang, H.L.[Hui-Ling], Wang, T.H.[Ting-Huai],
Primary object discovery and segmentation in videos via graph-based transductive inference,
CVIU(143), No. 1, 2016, pp. 159-172.
Elsevier DOI 1601
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Earlier: A2, A1:
Graph Transduction Learning of Object Proposals for Video Object Segmentation,
ACCV14(IV: 553-568).
Springer DOI 1504
Graph-based transductive inference BibRef

Li, C.L.[Cheng-Long], Lin, L.[Liang], Zuo, W.M.[Wang-Meng], Wang, W., Tang, J.[Jin],
An Approach to Streaming Video Segmentation With Sub-Optimal Low-Rank Decomposition,
IP(25), No. 5, May 2016, pp. 1947-1960.
IEEE DOI 1604
image representation BibRef

Xiao, H.X.[Hua-Xin], Kang, B.Y.[Bing-Yi], Liu, Y.[Yu], Zhang, M.J.[Mao-Jun], Feng, J.S.[Jia-Shi],
Online Meta Adaptation for Fast Video Object Segmentation,
PAMI(42), No. 5, May 2020, pp. 1205-1217.
IEEE DOI 2004
Adaptation models, Task analysis, Object segmentation, Optical imaging, Motion segmentation, Image segmentation, Runtime, convolutional neural networks BibRef

Jin, X.J.[Xiao-Jie], Li, X.[Xin], Xiao, H.X.[Hua-Xin], Shen, X.H.[Xiao-Hui], Lin, Z.[Zhe], Yang, J.M.[Ji-Mei], Chen, Y.P.[Yun-Peng], Dong, J.[Jian], Liu, L.Q.[Luo-Qi], Jie, Z.Q.[Ze-Qun], Feng, J.S.[Jia-Shi], Yan, S.C.[Shui-Cheng],
Video Scene Parsing with Predictive Feature Learning,
ICCV17(5581-5589)
IEEE DOI 1802
feature extraction, image classification, image representation, image segmentation, learning (artificial intelligence), Training BibRef

Li, C.L.[Cheng-Long], Lin, L.[Liang], Zuo, W.M.[Wang-Meng], Yan, S.C.[Shui-Cheng], Tang, J.[Jin],
SOLD: Sub-optimal low-rank decomposition for efficient video segmentation,
CVPR15(5519-5527)
IEEE DOI 1510
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Li, C.L.[Cheng-Long], Wang, X.[Xiao], Zhang, L.[Lei], Tang, J.[Jin], Wu, H.J.[He-Jun], Lin, L.[Liang],
Weighted Low-Rank Decomposition for Robust Grayscale-Thermal Foreground Detection,
CirSysVideo(27), No. 4, April 2017, pp. 725-738.
IEEE DOI 1704
Benchmark testing BibRef

Yang, S.[Sen], Luo, B.[Bin], Li, C.L.[Cheng-Long], Wang, G.Z.[Gui-Zhao], Tang, J.[Jin],
Fast Grayscale-Thermal Foreground Detection With Collaborative Low-Rank Decomposition,
CirSysVideo(28), No. 10, October 2018, pp. 2574-2585.
IEEE DOI 1811
Matrix decomposition, Sparse matrices, Videos, Collaboration, Gray-scale, Algorithm design and analysis, Object detection, edge-preserving filtering BibRef

Kim, S., Yang, D.W., Park, H.W.,
A Disparity-Based Adaptive Multihomography Method for Moving Target Detection Based on Global Motion Compensation,
CirSysVideo(26), No. 8, August 2016, pp. 1407-1420.
IEEE DOI 1609
cameras BibRef

Pérez-Rúa, J.M.[Juan-Manuel], Crivelli, T.[Tomas], Pérez, P.[Patrick],
Object-guided motion estimation,
CVIU(153), No. 1, 2016, pp. 88-99.
Elsevier DOI 1612
Optical flow BibRef

Pérez-Rúa, J.M.[Juan-Manuel], Crivelli, T.[Tomas], Pérez, P.[Patrick], Bouthemy, P.[Patrick],
Discovering motion hierarchies via tree-structured coding of trajectories,
BMVC16(xx-yy).
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And:
Hierarchical motion decomposition for dynamic scene parsing,
ICIP16(3952-3956)
IEEE DOI 1610
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And: A1, A2, A4, A3:
Determining Occlusions from Space and Time Image Reconstructions,
CVPR16(1382-1391)
IEEE DOI 1612
Cameras. Occlusions in frame-to-frame motion BibRef

Chen, L., Fan, L., Xie, G., Huang, K., Nüchter, A.,
Moving-Object Detection From Consecutive Stereo Pairs Using Slanted Plane Smoothing,
ITS(18), No. 11, November 2017, pp. 3093-3102.
IEEE DOI 1711
Cameras, Graphics processing units, Image segmentation, Motion segmentation, Optical imaging, Vehicle dynamics, Stereo vision, autonomous vehicles, BibRef

Zhang, Y.[Yun], Luo, B.[Bin], Zhang, L.P.[Liang-Pei],
Permutation Preference Based Alternate Sampling and Clustering for Motion Segmentation,
SPLetters(25), No. 3, March 2018, pp. 432-436.
IEEE DOI 1802
Segment tracking points belonging to different motions. Clustering algorithms, Couplings, Image color analysis, Motion segmentation, Shape, Tracking, sampling and clustering BibRef

Minaeian, S., Liu, J., Son, Y.J.,
Effective and Efficient Detection of Moving Targets From a UAV's Camera,
ITS(19), No. 2, February 2018, pp. 497-506.
IEEE DOI 1802
Cameras, Motion segmentation, Object detection, Optical imaging, Real-time systems, Robustness, Surveillance, Effectiveness, unmanned aerial vehicles BibRef

Chen, Y., Zou, W., Tang, Y., Li, X., Xu, C., Komodakis, N.,
SCOM: Spatiotemporal Constrained Optimization for Salient Object Detection,
IP(27), No. 7, July 2018, pp. 3345-3357.
IEEE DOI 1805
image motion analysis, image sequences, motion estimation, object detection, optimisation, spatiotemporal phenomena, spatiotemporal constraints BibRef

Yang, L., Han, J., Zhang, D., Liu, N., Zhang, D.,
Segmentation in Weakly Labeled Videos via a Semantic Ranking and Optical Warping Network,
IP(27), No. 8, August 2018, pp. 4025-4037.
IEEE DOI 1806
Image segmentation, Motion segmentation, Object segmentation, Optical imaging, Semantics, Task analysis, Videos, weak supervision BibRef

Fortun, D., Storath, M., Rickert, D., Weinmann, A., Unser, M.,
Fast Piecewise-Affine Motion Estimation Without Segmentation,
IP(27), No. 11, November 2018, pp. 5612-5624.
IEEE DOI 1809
image sequences, motion estimation, optimisation, piecewise constant techniques, piecewise constancy, piecewise affine BibRef

Wang, Y.Y.[Ying-Yan], Zeng, R.[Rui],
Image segmentation algorithm based on geometric flow Bandelets transformation particle replanting,
PRL(116), 2018, pp. 200-204.
Elsevier DOI 1812
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Garcia-Pedrero, A.[Angel], Gonzalo-Martín, C.[Consuelo], Lillo-Saavedra, M.[Mario], Rodríguez-Esparragón, D.[Dionisio],
The Outlining of Agricultural Plots Based on Spatiotemporal Consensus Segmentation,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
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Merino-Caviedes, S., Cordero-Grande, L., Pérez, M.T., Casaseca-de-la-Higuera, P., Martín-Fernández, M., Deriche, R., Alberola-López, C.,
A Second Order Multi-Stencil Fast Marching Method With a Non-Constant Local Cost Model,
IP(28), No. 4, April 2019, pp. 1967-1979.
IEEE DOI 1901
difference equations, finite difference methods, image processing, iterative methods, multi-stencil schemes BibRef

Wang, B.[Bin], Tang, S.[Sheng], Xiao, J.B.[Jun-Bin], Yan, Q.F.[Quan-Feng], Zhang, Y.D.[Yong-Dong],
Detection and tracking based tubelet generation for video object detection,
JVCIR(58), 2019, pp. 102-111.
Elsevier DOI 1901
Object detection, Tubelet generation, Tubelet fusion BibRef

Tokmakov, P.[Pavel], Schmid, C.[Cordelia], Alahari, K.[Karteek],
Learning to Segment Moving Objects,
IJCV(127), No. 3, March 2019, pp. 282-301.
Springer DOI 1903
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Earlier: A1, A3, A2:
Learning Video Object Segmentation with Visual Memory,
ICCV17(4491-4500)
IEEE DOI 1802
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Earlier: A1, A3, A2:
Learning Motion Patterns in Videos,
CVPR17(531-539)
IEEE DOI 1711
BibRef
Earlier: A1, A3, A2:
Weakly-Supervised Semantic Segmentation Using Motion Cues,
ECCV16(IV: 388-404).
Springer DOI 1611
neural nets, Visualization. Adaptive optics, Cameras, Decoding, Motion segmentation, Object segmentation, Videos BibRef

Bideau, P.[Pia], Learned-Miller, E.[Erik], Schmid, C.[Cordelia], Alahari, K.[Karteek],
The Right Spin: Learning Object Motion from Rotation-Compensated Flow Fields,
IJCV(132), No. 1, January 2024, pp. 40-55.
Springer DOI 2402
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Arn, R.T.[Robert T.], Narayana, P.[Pradyumna], Emerson, T.[Tegan], Draper, B.A.[Bruce A.], Kirby, M.[Michael], Peterson, C.[Chris],
Motion Segmentation via Generalized Curvatures,
PAMI(41), No. 12, December 2019, pp. 2919-2932.
IEEE DOI 1911
Motion segmentation, Approximation algorithms, Trajectory, Sensors, Noise measurement, video segmentation BibRef

Wang, Y.[Ye], Choi, J.M.[Jong-Moo], Zhang, K.[Kaitai], Huang, Q.[Qin], Chen, Y.[Yueru], Lee, M.S.[Ming-Sui], Kuo, C.C.J.[C.C. Jay],
Video object tracking and segmentation with box annotation,
SP:IC(85), 2020, pp. 115858.
Elsevier DOI 2005
Video object tracking, Video object segmentation, Reverse optimization, Bounding box annotation BibRef

Li, S.Y.[Si-Yang], Seybold, B.[Bryan], Vorobyov, A.[Alexey], Lei, X.J.[Xue-Jing], Kuo, C.C.J.[C.C. Jay],
Unsupervised Video Object Segmentation with Motion-Based Bilateral Networks,
ECCV18(III: 215-231).
Springer DOI 1810
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Wang, Y.[Ye], Choi, J.M.[Jong-Moo], Chen, Y.[Yueru], Li, S.Y.[Si-Yang], Huang, Q.[Qin], Zhang, K.[Kaitai], Lee, M.S.[Ming-Sui], Kuo, C.C.J.[C.C. Jay],
Unsupervised video object segmentation with distractor-aware online adaptation,
JVCIR(74), 2021, pp. 102953.
Elsevier DOI 2101
BibRef
Earlier: A1, A2, A3, A5, A4, A7, A8, Only:
Design Pseudo Ground Truth with Motion Cue for Unsupervised Video Object Segmentation,
ACCV18(IV:518-533).
Springer DOI 1906
Unsupervised video object segmentation, Pseudo ground truth, Motion saliency, Hard negative mining, Online adaptation BibRef

Sharma, K.[Krishan], Rameshan, R.[Renu],
Distance based kernels for video tensors on product of Riemannian matrix manifolds,
JVCIR(75), 2021, pp. 103045.
Elsevier DOI 2103
Video tensor, Product manifold geometry, Sparse representation, Grassmann manifold, SPD manifold, Riemannian manifold, Kernel methods BibRef

Xu, C.Y.[Chun-Yan], Wei, L.[Li], Cui, Z.[Zhen], Zhang, T.[Tong], Yang, J.[Jian],
Meta-VOS: Learning to Adapt Online Target-Specific Segmentation,
IP(30), 2021, pp. 4760-4772.
IEEE DOI 2105
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Kutbi, M.[Mohammed], Chang, Y.Z.[Yi-Zhe], Mordohai, P.[Philippos],
Inlier clustering based on the residuals of random hypotheses,
PRL(150), 2021, pp. 101-107.
Elsevier DOI 2109
Motion segmentation, Model estimation, Clustering BibRef

Qi, J.Y.[Ji-Yang], Gao, Y.[Yan], Hu, Y.[Yao], Wang, X.G.[Xing-Gang], Liu, X.Y.[Xiao-Yu], Bai, X.[Xiang], Belongie, S.[Serge], Yuille, A.L.[Alan L.], Torr, P.H.S.[Philip H. S.], Bai, S.[Song],
Occluded Video Instance Segmentation: A Benchmark,
IJCV(130), No. 8, August 2022, pp. 2022-2039.
Springer DOI 2207
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Yu, R.[Ran], Tian, C.Y.[Chen-Yu], Xia, W.H.[Wei-Hao], Zhao, X.Y.[Xin-Yuan], Wang, L.J.[Lie-Jun], Yang, Y.J.[Yu-Jiu],
Real-time human-centric segmentation for complex video scenes,
IVC(126), 2022, pp. 104552.
Elsevier DOI 2209
Multiple human tracking, Video instance segmentation, One-stage detector, Video understanding, Deep neural networks BibRef

Dong, S.H.[Shao-Hua], Zhou, W.[Wujie], Qian, X.H.[Xiao-Hong], Yu, L.[Lu],
GEBNet: Graph-Enhancement Branch Network for RGB-T Scene Parsing,
SPLetters(29), 2022, pp. 2273-2277.
IEEE DOI 2212
Semantics, Convolution, Fuses, Feature extraction, Real-time systems, Deep learning, graph neural network, scene parsing BibRef

Meunier, E.[Etienne], Badoual, A.[Anaïs], Bouthemy, P.[Patrick],
EM-Driven Unsupervised Learning for Efficient Motion Segmentation,
PAMI(45), No. 4, April 2023, pp. 4462-4473.
IEEE DOI 2303
Motion segmentation, Image segmentation, Optical imaging, Object segmentation, Training, Cameras, multiple motion segmentation BibRef

Lin, S.Y.[Shu-Yuan], Yang, A.[Anjia], Lai, T.[Taotao], Weng, J.[Jian], Wang, H.Z.[Han-Zi],
Multi-Motion Segmentation via Co-Attention-Induced Heterogeneous Model Fitting,
CirSysVideo(34), No. 3, March 2024, pp. 1786-1798.
IEEE DOI 2403
Motion segmentation, Adaptation models, Sparse matrices, Tracking, Correlation, Computational modeling, Parameter estimation, surface fitting BibRef

Liao, J.H.[Jun-Hua], Duan, H.[Haihan], Zhao, W.[Wanbing], Feng, K.H.[Kang-Hui], Yang, Y.B.[Yan-Bing], Chen, L.Y.[Liang-Yin],
A Video Shot Occlusion Detection Algorithm Based on the Abnormal Fluctuation of Depth Information,
CirSysVideo(34), No. 3, March 2024, pp. 1627-1640.
IEEE DOI Code:
WWW Link. 2403
Task analysis, Estimation, Detection algorithms, Neural networks, Fluctuations, Robustness, Training, Dataset, occlusion detection, automatic video editing BibRef

Cheng, C.[Chen], Xu, H.[Huahu],
A 3D motion image recognition model based on 3D CNN-GRU model and attention mechanism,
IVC(146), 2024, pp. 104991.
Elsevier DOI 2405
Graph convolutional networks, Cross-graph convolution operation, Residual connections, 3D CNN BibRef

Liang, Y.Q.[Yi-Qing], Laidlaw, E.[Eliot], Meyerowitz, A.[Alexander], Sridhar, S.[Srinath], Tompkin, J.[James],
Semantic Attention Flow Fields for Monocular Dynamic Scene Decomposition,
ICCV23(21740-21749)
IEEE DOI Code:
WWW Link. 2401
BibRef

Wu, H.Q.[Hao-Qian], Chen, K.Y.[Ke-Yu], Luo, Y.[Yanan], Qiao, R.Z.[Rui-Zhi], Ren, B.[Bo], Liu, H.Z.[Hao-Zhe], Xie, W.C.[Wei-Cheng], Shen, L.L.[Lin-Lin],
Scene Consistency Representation Learning for Video Scene Segmentation,
CVPR22(14001-14010)
IEEE DOI 2210
Representation learning, Measurement, Protocols, TV, Semantics, Self-supervised learning, Motion pictures, Self- semi- meta- unsupervised learning BibRef

Lin, H.[Huaijia], Wu, R.Z.[Rui-Zheng], Liu, S.[Shu], Lu, J.B.[Jiang-Bo], Jia, J.Y.[Jia-Ya],
Video Instance Segmentation with a Propose-Reduce Paradigm,
ICCV21(1719-1728)
IEEE DOI 2203
Image segmentation, Head, Merging, Benchmark testing, Robustness, Task analysis, Video analysis and understanding, grouping and shape BibRef

Du, W.T.[Wen-Tao], Xiang, Z.Y.[Zhi-Yu], Chen, S.Y.[Shu-Ya], Qiao, C.Y.[Cheng-Yu], Chen, Y.[Yiman], Bai, T.M.[Ting-Ming],
Real-time Instance Segmentation with Discriminative Orientation Maps,
ICCV21(7294-7303)
IEEE DOI 2203
Codes, Filtering, Detectors, Benchmark testing, Prediction algorithms, Real-time systems, Segmentation, BibRef

Yang, S.[Shusheng], Fang, Y.X.[Yu-Xin], Wang, X.G.[Xing-Gang], Li, Y.[Yu], Fang, C.[Chen], Shan, Y.[Ying], Feng, B.[Bin], Liu, W.Y.[Wen-Yu],
Crossover Learning for Fast Online Video Instance Segmentation,
ICCV21(8023-8032)
IEEE DOI 2203
Visualization, Codes, Computational modeling, Benchmark testing, Task analysis, Context modeling, BibRef

Wang, T.[Tao], Xu, N.[Ning], Chen, K.[Kean], Lin, W.Y.[Wei-Yao],
End-to-End Video Instance Segmentation via Spatial-Temporal Graph Neural Networks,
ICCV21(10777-10786)
IEEE DOI 2203
Image segmentation, Head, Image edge detection, Feature extraction, Information filters, Graph neural networks, Motion and tracking, Video analysis and understanding BibRef

Wang, Y.Q.[Yu-Qing], Xu, Z.L.[Zhao-Liang], Wang, X.L.[Xin-Long], Shen, C.H.[Chun-Hua], Cheng, B.S.[Bao-Shan], Shen, H.[Hao], Xia, H.X.[Hua-Xia],
End-to-End Video Instance Segmentation with Transformers,
CVPR21(8737-8746)
IEEE DOI 2111
Image segmentation, Computational modeling, Pipelines, Transformer cores, Transformers, Pattern recognition BibRef

Liu, D.F.[Dong-Fang], Cui, Y.M.[Yi-Ming], Tan, W.B.[Wen-Bo], Chen, Y.J.[Ying-Jie],
SG-Net: Spatial Granularity Network for One-Stage Video Instance Segmentation,
CVPR21(9811-9820)
IEEE DOI 2111
Runtime, Tracking, Predictive models, Feature extraction, Robustness BibRef

Li, M.[Minghan], Li, S.[Shuai], Li, L.[Lida], Zhang, L.[Lei],
Spatial Feature Calibration and Temporal Fusion for Effective One-stage Video Instance Segmentation,
CVPR21(11210-11219)
IEEE DOI 2111
Convolutional codes, Correlation, Sensitivity, Tracking, Motion segmentation, Redundancy BibRef

Liu, Q.[Qing], Ramanathan, V.[Vignesh], Mahajan, D.[Dhruv], Yuille, A.L.[Alan L.], Yang, Z.[Zhenheng],
Weakly Supervised Instance Segmentation for Videos with Temporal Mask Consistency,
CVPR21(13963-13973)
IEEE DOI 2111
Training, Measurement, Image segmentation, Costs, Motion segmentation, Computational modeling BibRef

Xiong, S., Li, S., Kou, L., Guo, W., Zhou, Z., Zhao, Z.,
Td-VOS: Tracking-Driven Single-Object Video Object Segmentation,
ICIVC20(102-107)
IEEE DOI 2009
Object segmentation, Image segmentation, Object tracking, Head, Motion segmentation, Task analysis, Target tracking, DAVIS2016 BibRef

Mitrokhin, A., Hua, Z., Fermüller, C., Aloimonos, Y.,
Learning Visual Motion Segmentation Using Event Surfaces,
CVPR20(14402-14411)
IEEE DOI 2008
Cameras, Optical sensors, Trajectory, Shape, Optical imaging, Task analysis BibRef

Ranjan, A.[Anurag], Jampani, V.[Varun], Balles, L.[Lukas], Kim, K.[Kihwan], Sun, D.Q.[De-Qing], Wulff, J.[Jonas], Black, M.J.[Michael J.],
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation,
CVPR19(12232-12241).
IEEE DOI 2002
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Malekzadeh, M., Javanmard, R., Karimipour, F.,
Extracting Point of Interests From Movement Data Using Kernel Density And Weighted K-means,
SMPR19(717-720).
DOI Link 1912
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Xu, X., Cheong, L.F., Li, Z.,
Motion Segmentation by Exploiting Complementary Geometric Models,
CVPR18(2859-2867)
IEEE DOI 1812
Transmission line matrix methods, Motion segmentation, Adaptation models, Numerical models, Benchmark testing BibRef

Kalboussi, R.[Rahma], Abdellaoui, M.[Mehrez], Douik, A.[Ali],
Detecting and Recognizing Salient Object in Videos,
ACIVS18(62-73).
Springer DOI 1810
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Xu, N.[Ning], Yang, L.J.[Lin-Jie], Fan, Y.C.[Yu-Chen], Yang, J.C.[Jian-Chao], Yue, D.C.[Ding-Cheng], Liang, Y.C.[Yu-Chen], Price, B.L.[Brian L.], Cohen, S.[Scott], Huang, T.S.[Thomas S.],
YouTube-VOS: Sequence-to-Sequence Video Object Segmentation,
ECCV18(VI: 603-619).
Springer DOI 1810
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Ci, H.[Hai], Wang, C.Y.[Chun-Yu], Wang, Y.Z.[Yi-Zhou],
Video Object Segmentation by Learning Location-Sensitive Embeddings,
ECCV18(XI: 524-539).
Springer DOI 1810
BibRef

Chen, D.J., Chen, H.T., Chang, L.W.,
Video segmentation via boundary-aware flow,
ICIP17(3340-3344)
IEEE DOI 1803
Estimation, Integrated optics, Motion segmentation, Object segmentation, Optical imaging, Optical propagation, transductive inference BibRef

Zhu, X., Xiong, Y., Dai, J., Yuan, L., Wei, Y.,
Flow-Guided Feature Aggregation for Video Object Detection,
ICCV17(408-417)
IEEE DOI 1802
BibRef
And:
Deep Feature Flow for Video Recognition,
CVPR17(4141-4150)
IEEE DOI 1711
feature extraction, image motion analysis, learning (artificial intelligence), object detection, Training. Convolutional codes, Image recognition, Image segmentation, Optical imaging, Semantics BibRef

Zhao, W.[Wei], Roos, N.[Nico], Peeters, R.[Ralf],
3D Motion Consistency Analysis for Segmentation in 2D Video Projection,
CAIP17(II: 440-452).
Springer DOI 1708
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Cordes, K.[Kai], Ray’onaldo, C.[Christopherus], Broszio, H.[Hellward],
Motion-Coherent Affinities for Hypergraph Based Motion Segmentation,
CAIP17(I: 121-132).
Springer DOI 1708
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Vongkulbhisal, J.[Jayakorn], Cabral, R.S.[Ricardo S.], de la Torre, F.[Fernando], Costeira, J.P.[João P.],
Motion from Structure (MfS): Searching for 3D Objects in Cluttered Point Trajectories,
CVPR16(5639-5647)
IEEE DOI 1612
Use 3D models to detect moving objects. BibRef

Luiten, J.[Jonathon], Voigtlaender, P.[Paul], Leibe, B.[Bastian],
PReMVOS: Proposal-Generation, Refinement and Merging for Video Object Segmentation,
ACCV18(IV:565-580).
Springer DOI 1906
BibRef

Kontogianni, T.[Theodora], Mathias, M.[Markus], Leibe, B.[Bastian],
Incremental Object Discovery in Time-Varying Image Collections,
CVPR16(2082-2090)
IEEE DOI 1612
Limited Horizon Minimum Spanning Tree. BibRef

Perazzi, F.[Federico], Pont-Tuset, J., McWilliams, B., Van Gool, L.J., Gross, M., Sorkine-Hornung, A.[Alexander],
A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation,
CVPR16(724-732)
IEEE DOI 1612
Dataset, Video Segmentation. BibRef

Xiao, F., Lee, Y.J.,
Track and Segment: An Iterative Unsupervised Approach for Video Object Proposals,
CVPR16(933-942)
IEEE DOI 1612
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Perazzi, F.[Federico], Khoreva, A., Benenson, R., Schiele, B., Sorkine-Hornung, A.[Alexander],
Learning Video Object Segmentation from Static Images,
CVPR17(3491-3500)
IEEE DOI 1711
Image segmentation, Labeling, Object segmentation, Proposals, Strain, Training BibRef

Märki, N.[Nicolas], Perazzi, F.[Federico], Wang, O.[Oliver], Sorkine-Hornung, A.[Alexander],
Bilateral Space Video Segmentation,
CVPR16(743-751)
IEEE DOI 1612
BibRef

Perazzi, F.[Federico], Wang, O.[Oliver], Grosse, M.[Max], Sorkine-Hornung, A.[Alexander],
Fully Connected Object Proposals for Video Segmentation,
ICCV15(3227-3234)
IEEE DOI 1602
Computer vision BibRef

Nagaraja, N.S., Schmidt, F.R., Brox, T.,
Video Segmentation with Just a Few Strokes,
ICCV15(3235-3243)
IEEE DOI 1602
Benchmark testing BibRef

Yang, M.Y.[Michael Ying], Feng, S.[Sitong], Rosenhahn, B.[Bodo],
Sparse Optimization for Motion Segmentation,
VSegCV14(375-389).
Springer DOI 1504
BibRef

Gray, C.[Charles], James, S.[Stuart], Collomosse, J.P.[John P.], Asente, P.[Paul],
A particle filtering approach to salient video object localization,
ICIP14(194-198)
IEEE DOI 1502
Cameras BibRef

Pu, S.T.[Song-Tao], Zha, H.B.[Hong-Bin],
Sandwich Cut: An Algorithm for Temporally-Coherent Video Bilayer Segmentation,
ICPR14(1061-1066)
IEEE DOI 1412
Adaptive optics BibRef

Hu, H.[Han], Lin, Z.C.[Zhou-Chen], Feng, J.J.[Jian-Jiang], Zhou, J.[Jie],
Smooth Representation Clustering,
CVPR14(3834-3841)
IEEE DOI 1409
motion segmentation, representation, subspace clustering BibRef

Ji, P.[Pan], Li, H.D.[Hong-Dong], Salzmann, M.[Mathieu], Dai, Y.C.[Yu-Chao],
Robust Motion Segmentation with Unknown Correspondences,
ECCV14(VI: 204-219).
Springer DOI 1408
BibRef

Chacon-Murguia, M.I., Ramirez-Quintana, J.A., Ramirez-Alonso, G.,
Evaluation of the background modeling method Auto-Adaptive Parallel Neural Network Architecture in the SBMnet dataset,
ICPR16(137-142)
IEEE DOI 1705
Adaptation models, Analytical models, Classification algorithms, Computational modeling, Heuristic algorithms, Image color analysis, Videos, background modeling, neural video analysis, video, analysis BibRef

Ramirez-Alonso, G., Chacon-Murguia, M.I.,
Segmentation of dynamic objects in video sequences fusing the strengths of a background subtraction model, optical flow and matting algorithms,
Southwest14(33-36)
IEEE DOI 1406
image segmentation BibRef

Banica, D., Agape, A., Ion, A., Sminchisescu, C.,
Video Object Segmentation by Salient Segment Chain Composition,
PGMs13(283-290)
IEEE DOI 1403
image colour analysis BibRef

Verleysen, C.[Cédric], de Vleeschouwer, C.[Christophe],
Learning and Propagation of Dominant Colors for Fast Video Segmentation,
ACIVS13(657-668).
Springer DOI 1311
BibRef

Min, K.[Kyle], Corso, J.J.[Jason J.],
TASED-Net: Temporally-Aggregating Spatial Encoder-Decoder Network for Video Saliency Detection,
ICCV19(2394-2403)
IEEE DOI 2004
convolutional neural nets, decoding, feature extraction, image representation, image resolution, image sequences, Convolution BibRef

Griffin, B.[Brent], Corso, J.J.[Jason J.],
Tukey-Inspired Video Object Segmentation,
WACV19(1723-1733)
IEEE DOI 1904
image annotation, image motion analysis, image segmentation, unsupervised learning, video signal processing, Benchmark testing BibRef

Xu, C.L.[Chen-Liang], Corso, J.J.[Jason J.],
Evaluation of super-voxel methods for early video processing,
CVPR12(1202-1209).
IEEE DOI 1208
Evaluate 5 methods aggregation, graph, hierarchical graph, mean shift, normalized cuts. BibRef

Bertasius, G.[Gedas], Torresani, L.[Lorenzo], Shi, J.B.[Jian-Bo],
Object Detection in Video with Spatiotemporal Sampling Networks,
ECCV18(XII: 342-357).
Springer DOI 1810
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Fragkiadaki, K.[Katerina], Zhang, G.[Geng], Shi, J.B.[Jian-Bo],
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CVPR12(1846-1853).
IEEE DOI 1208
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Kim, J.S.[Jong-Sung], Jeong, I.K.[Il-Kwon],
Motion Segmentation Using Divisive Graph Cuts,
MVA09(406-).
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Ubukata, T.[Toru], Terabayashi, K.[Kenji], Moro, A.[Alessandro], Umeda, K.[Kazunori],
Multi-object Segmentation in a Projection Plane Using Subtraction Stereo,
ICPR10(3296-3299).
IEEE DOI 1008
extract the foreground objetct with stereo. BibRef

Li, P.[Peng], Wang, C.[Cheng], Wang, H.[Han],
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Bachmann, A.[Alexander], Lulcheva, I.[Irina],
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VS09(1216-1221).
IEEE DOI 0910
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Bachmann, A.[Alexander], Kuehne, H.[Hildegard],
An iterative scheme for motion-based scene segmentation,
WDV09(735-742).
IEEE DOI 0910
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Kang, H.W.[Hong-Wen], Efros, A.A.[Alexei A.], Hebert, M.[Martial], Kanade, T.[Takeo],
Image composition for object pop-out,
3DRR09(681-688).
IEEE DOI 0910
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Kang, Y.S.[You-Sun], Yamaguchi, K.[Koichiro], Naito, T.[Takashi], Ninomiya, Y.[Yoshiki],
Road scene labeling using SfM module and 3D bag of textons,
3DRR09(657-664).
IEEE DOI 0910
Relate 3D spatial (SfM) with 2D segmentation. BibRef

Kuchnio, P.[Peter], Capson, D.W.[David W.],
A parallel mapping of optical flow to Compute Unified Device Architecture for motion-based image segmentation,
ICIP09(2325-2328).
IEEE DOI 0911
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Kim, J.H.[Jae-Hak], Agapito, L.[Lourdes],
Motion segmentation using the Hadamard product and spectral clustering,
WMVC09(1-8).
IEEE DOI 0912
BibRef

Huang, Y.C.[Yu-Chi], Liu, Q.S.[Qing-Shan], Metaxas, D.N.[Dimitris N.],
Video object segmentation by hypergraph cut,
CVPR09(1738-1745).
IEEE DOI 0906
Oversegment, then graph structure of patch relations. BibRef

Yang, W.M.[Wen-Ming], Lu, W.[Wang], Zhang, N.T.[Nai-Tong],
Object Extraction Combining Image Partition with Motion Detection,
ICIP07(III: 337-340).
IEEE DOI 0709
BibRef

del-Blanco, C.R.[Carlos R.], Garcia, N.[Narciso], Salgado, L.[Luis], Jaureguizar, F.[Fernando],
Object Tracking from Unstabilized Platforms by Particle Filtering with Embedded Camera Ego Motion,
AVSBS09(400-405).
IEEE DOI 0909
BibRef

del-Blanco, C.R.[Carlos R.], Jaureguizar, F.[Fernando], Salgado, L.[Luis], García, N.[Narciso],
Target Detection Through Robust Motion Segmentation and Tracking Restrictions in Aerial FLIR Images,
ICIP07(V: 445-448).
IEEE DOI 0709
BibRef
And:
Aerial Moving Target Detection Based on Motion Vector Field Analysis,
ACIVS07(990-1001).
Springer DOI 0708

See also Automatic Feature-Based Stabilization of Video with Intentional Motion through a Particle Filter. BibRef

Chen, C.[Cheng], Fan, G.L.[Guo-Liang],
What Can We Learn from Biological Vision Studies for Human Motion Segmentation?,
ISVC06(II: 790-801).
Springer DOI 0611
BibRef

Ahmed, R.[Rakib], Karmakar, G.C.[Gour C.], Dooley, L.S.[Laurence S.],
Incorporation of Texture Information for Joint Spatio-Temporal Probabilistic Video Object Segmentation,
ICIP07(VI: 293-296).
IEEE DOI 0709
BibRef
Earlier:
Region-Based Shape Incorporation for Probabilistic Spatio-Temporal Video Object Segmentation,
ICIP06(2445-2448).
IEEE DOI 0610
BibRef

Dorea, C.C., Paraas, M., Marqees, F.,
Generation of Long-Term Color and Motion Coherent Partitions,
ICIP06(581-584).
IEEE DOI 0610
BibRef

Torsello, A.[Andrea], Pavan, M.[Massimiliano], Pelillo, M.[Marcello],
Spatio-temporal Segmentation Using Dominant Sets,
EMMCVPR05(301-315).
Springer DOI 0601

See also Dominant Sets and Pairwise Clustering. BibRef

Singaraju, D.[Dheeraj], Vidal, R.[René],
Direct Segmentation of Multiple 2-D Motion Models of Different Types,
WDV06(18-33).
Springer DOI 0705
BibRef
And:
A Bottom up Algebraic Approach to Motion Segmentation,
ACCV06(I:286-296).
Springer DOI 0601
BibRef

Benboudjema, D., Pieczynski, W.,
Segmenting Non Stationary Images with Triplet Markov Fields,
ICIP05(I: 317-320).
IEEE DOI 0512
BibRef

Galun, M.[Meirav], Apartsin, A.[Alexander], Basri, R.[Ronen],
Multiscale Segmentation by Combining Motion and Intensity Cues,
CVPR05(I: 256-263).
IEEE DOI 0507
BibRef

Saez, E., Benavides, J.L., Guil, N.,
Combining luminance and edge based metrics for robust temporal video segmentation,
ICIP04(IV: 2231-2234).
IEEE DOI 0505
BibRef

Farmer, M.E., Lu, X.G.[Xiao-Guang], Chen, H.[Hong], Jain, A.K.[Anil K.],
Robust motion-based image segmentation using fusion,
ICIP04(V: 3375-3378).
IEEE DOI 0505
BibRef

Besbes, O., Belhadj, Z.,
Multiple motion segmentation with level sets without prior information,
ICIP04(I: 369-372).
IEEE DOI 0505
BibRef

Jia, Z.[Zhen], Balasuriya, A.[Arjuna],
Motion Based Image Segmentation with Unsupervised Bayesian Learning,
Motion05(II: 2-7).
IEEE DOI 0502
BibRef

Wang, H., Culverhouse, P.F.,
Robust Motion Segmentation by Spectral Clustering,
BMVC03(xx-yy).
HTML Version. 0409
BibRef

Majchrzak, D., Sarkar, S.,
Parallelizing motion segmentation by perceptual organization of XYT,
ICPR04(I: 773-776).
IEEE DOI 0409
BibRef

Park, J.H.[Jin-Hyeong], Zha, H.Y.[Hong-Yuan], Kasturi, R.[Rangachar],
Spectral Clustering for Robust Motion Segmentation,
ECCV04(Vol IV: 390-401).
Springer DOI 0405
BibRef

Wang, J.[Jue], Thiesson, B.[Bo], Xu, Y.Q.[Ying-Qing], Cohen, M.[Michael],
Image and Video Segmentation by Anisotropic Kernel Mean Shift,
ECCV04(Vol II: 238-249).
Springer DOI 0405
BibRef

Krajsek, K.[Kai], Mester, R.[Rudolf],
On the equivalence of variational and statistical differential motion estimation,
Southwest06(11-15).
IEEE DOI 0603
BibRef

Mester, R.[Rudolf],
A Bayesian view on matching and motion estimation,
Southwest12(197-200).
IEEE DOI 1205
BibRef

Ochs, M.[Matthias], Bradler, H.[Henry], Mester, R.[Rudolf],
Enhanced Phase Correlation for Reliable and Robust Estimation of Multiple Motion Distributions,
PSIVT15(368-379).
Springer DOI 1602
BibRef

Mester, R.[Rudolf],
Motion estimation revisited: an estimation-theoretic approach,
Southwest14(113-116)
IEEE DOI 1406
BibRef
Earlier:
The generalization, optimization, and information-theoretic justification of filter-based and autocovariance-based motion estimation,
ICIP03(III: 81-84).
IEEE DOI 0312
BibRef
Earlier:
A New View at Differential and Tensor-Based Motion Estimation Schemes,
DAGM03(321-329).
Springer DOI 0310
BibRef
Earlier:
A system-theoretical view on local motion estimation,
Southwest02(201-205).
IEEE Top Reference. 0208
approximation theory BibRef

El Saban, M.A., Manjunath, B.S.,
Video region segmentation by spatio-temporal watersheds,
ICIP03(I: 349-352).
IEEE DOI 0312
BibRef

Fu, M.F.[Ming Fai], Au, O.C., Chan, W.C.[Wing Cheong],
Fast global motion estimation based on local motion segmentation,
ICIP03(II: 367-370).
IEEE DOI 0312
BibRef

Silveira, M., Piedade, M.,
MRF-motion Segmentation Based on Dominant Motion Estimation and the Detection of Uncovered Regions,
ICIP01(I: 373-376).
IEEE DOI 0108
BibRef

Silveira, M., Piedade, M.,
Joint segmentation and motion estimation,
ICIP98(II: 657-661).
IEEE DOI 9810
BibRef

Lindh, P., van den Branden Lambrecht, C.[Christian],
Efficient Spatio-Temporal Decomposition for Perceptual Processing of Video Sequences,
ICIP96(III: 331-334).
IEEE DOI BibRef 9600

Mills, S., Novins, K.,
Motion Segmentation in Long Image Sequences,
BMVC00(xx-yy).
PDF File. 0009
BibRef

Nitsuwat, S., Jin, J.,
Motion-based Video Segmentation Using Fuzzy Clustering and Classical Mixture Model,
ICIP00(Vol I: 300-303).
IEEE DOI 0008
BibRef

Sun, H.Z.[Hong-Zan], Feng, T.[Tao], Tan, T.N.[Tie-Niu],
Spatio-temporal Segmentation for Video Surveillance,
ICPR00(Vol I: 843-846).
IEEE DOI 0009
BibRef

Sista, S., Kashyap, R.L.,
Unsupervised Video Segmentation and Object Tracking,
ICIP99(26PP6). Not in proceedings. BibRef 9900

Fermüller, C.[Cornelia], Brodsky, T.[Tomas], Aloimonos, Y.F.[Yi-Fannis],
Motion Segmentation: A Synergistic Approach,
CVPR99(II:226-231a).
IEEE DOI BibRef 9900

Fermüller, C.[Cornelia], Defoort, F.P.[Filip P.], and Aloimonos, Y.F.[Yi-Fannis],
Motion Segmentation for a Binocular Observer,
UMD--TR3893, April 1998. Motion segmentation and camera motion estimation solved together for binocular observer. Uses scene smoothness.
WWW Link. BibRef 9804

Thirde, D.J., Jones, G.A.,
Hierarchical probabilistic models for video object segmentation and tracking,
ICPR04(I: 636-639).
IEEE DOI 0409
BibRef

Thirde, D.J., Jones, G.A., Flack, J.,
Spatio-Temporal Semantic Object Segmentation using Probabilistic Sub-Object Regions,
BMVC03(xx-yy).
HTML Version. 0409
BibRef

Giaccone, P.R., Jones, G.A.,
Segmentation of Global Motion using Temporal Probabilistic Classification,
BMVC98(xx-yy). BibRef 9800

Kim, W.S.[Won Sup], Lee, S.W.[Seong-Whan], Han, S.K.[Seung Kee], Kook, H.[Hyungtae],
Temporal Segmentation and Selective Attention in the Stochastic Oscillator Neural Network,
ICPR98(Vol I: 259-261).
IEEE DOI 9808
BibRef

Shi, J.B.[Jian-Bo], and Malik, J.[Jitendra],
Motion Segmentation and Tracking Using Normalized Cuts,
ICCV98(1154-1160).
IEEE DOI
See also Normalized Cuts and Image Segmentation. BibRef 9800

Morier, F., Nicolas, H., Benois-Pineau, J., Barba, D., Sanson, H.,
Relative depth estimation of video objects for image interpolation,
ICIP98(I: 953-957).
IEEE DOI 9810

See also Hierarchical Segmentation of Video Sequences for Content Manipulation and Adaptive Coding. BibRef

Martinez, F.X., Benois-Pineeau, J., Barba, D.,
Extraction of the relative depth information of objects in video sequences,
ICIP98(I: 948-952).
IEEE DOI 9810
BibRef

Kong, M.Q.[Ming-Qi], Leduc, J.P., Ghosh, B.K., Wickerhauser, M.V.,
Spatio-temporal continuous wavelet transforms for motion-based segmentation in real image sequences,
ICIP98(II: 662-666).
IEEE DOI 9810
BibRef

Wilson, R., Meulemans, P., Calway, A.D., Kruger, S.,
Image sequence analysis and segmentation using G-blobs,
ICIP98(II: 483-487).
IEEE DOI 9810
BibRef

Strens, M., and Boyce, J.,
Constraint Directed Learning for Unsupervised Image Sequence Segmentation,
ICIP97(I: 743-746).
IEEE DOI BibRef 9700

Herodotou, N., Venetsanopoulos, A.N.,
Temporal prediction of video sequences using an image warping technique based on color segmentation,
CIAP97(I: 494-501).
Springer DOI 9709
BibRef

Li, Y.[Yi], Hatzinakos, D.[Dimitrios], Venetsanopoulos, A.N.[Anastasios N.],
A Multi-Frame, Region-Feature Based Technique for Motion Segmentation,
ICIP99(I:11-15).
IEEE DOI BibRef 9900

Chalom, E.[Edmond], Bove, V.M.[V. Michael],
Segmentation of an Image Sequence Using Multi-Dimensional image attributes,
ICIP96(II: 525-528).
IEEE DOI BibRef 9600

Duc, B.[Benoît], Schroeter, P.[Philippe], Bigün, J.[Josef],
Motion Segmentation by Fuzzy Clustering with Automatic Determination of the Number of Motions,
ICPR96(IV: 376-380).
IEEE DOI 9608
BibRef
And:
Motion Estimation and Segmentation by Fuzzy Algorithms,
ICIP95(III: 472-475).
IEEE DOI 9510
BibRef
And:
Spatio-temporal robust motion estimation and segmentation,
CAIP95(238-245).
Springer DOI 9509
(Swiss Federal Inst. of Technology, CH) BibRef

Duc, B.[Benoît],
Motion estimation using invariance under group transformations,
ICPR94(A:159-163).
IEEE DOI 9410
BibRef

Konrad, J., Dang, V.N.,
Coding-Oriented Video Segmentation Inspired by MRF Models,
ICIP96(I: 909-912).
IEEE DOI BibRef 9600

Cheong, C.K.[Cha Keon], Aizawa, K.[Kiyoharu],
Structural Motion Segmentation Based on Probabilistic Clustering,
ICIP96(I: 505-508).
IEEE DOI BibRef 9600

Xu, G.[Gang], Tsuji, S.,
Correspondence and segmentation of multiple rigid motions via epipolar geometry,
ICPR96(I: 213-217).
IEEE DOI 0509
BibRef

Charan, R., Ahuja, N.,
Feature Guided Pixel Matching and Segmentation in Motion Image Sequences,
SCV95(277-282).
IEEE DOI University of Illinois at Urbana-Champaign. Multi-grid approach, find pixels through the sequence, segment into different motions. BibRef 9500

Saito, T., Komatsu, T., Akimoto, Y.,
Global motion segmentation for mid-level representation of moving images,
ICIP95(II: 402-405).
IEEE DOI 9510
BibRef

Saito, T.[Takahiro], Komatsu, T.[Takashi],
Motion analysis and segmentation for object-oriented mid-level image representation,
CIAP95(663-668).
Springer DOI 9509
BibRef

Ben-Ezra, M.[Moshe], Peleg, S.[Shmuel], and Rousso, B.[Benny],
Motion Segmentation Using Convergence Properties,
ARPA94(II:1233-1235). BibRef 9400

Desmet, S., Deknuydt, B., van Eycken, L.[Luc], Oosterlinck, A.,
Initial segmentation of a scene using the results of a classification based motion estimator,
ICIP94(I: 559-562).
IEEE DOI 9411
BibRef

Yamamoto, M.,
A Segmentation Method Based on Motion from Image Sequence and Depth,
ICPR90(I: 230-232).
IEEE DOI BibRef 9000

Sinclair, D.A.,
Motion Segmentation and Local Structure,
ICCV93(366-373).
IEEE DOI Accumulate estimates of the structure from flow normals. BibRef 9300

Sinclair, D.A., Blake, A.[Andrew], Beardsley, P.A.[Paul A.], Murray, D.W.[David W.],
A Novel Approach to Motion Segmentation,
BMVC91(xx-yy).
PDF File. 9109
BibRef

Gong, S.G.[Shao-Gang], Buxton, H.[Hilary],
From Contextual Knowledge to Computational Constraints,
BMVC93(229-238)
PDF File. 9309
(QMW, London and Sussex Univ) Was given as: Bayesian Net for Mapping Contextual Knowledge to Computational Constraints in Motion Segmentation and Tracking. BibRef

Gambotto, J.P.,
A region-based spatio-temporal segmentation algorithm,
ICPR92(III:189-192).
IEEE DOI 9208
BibRef

Marchant, J.A.,
Accurate Boundary Location from Motion,
BMVC92(xx-yy).
PDF File. 9209
BibRef

Peleg, S., and Rom, H.,
Motion Based Segmentation,
ICPR90(I: 109-113).
IEEE DOI BibRef 9000

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Motion Detection, Analysis of Motion Detectors .