Bugeau, A.[Aurelie],
Perez, P.[Patrick],
Detection and segmentation of moving objects in complex scenes,
CVIU(113), No. 4, April 2009, pp. 459-476.
Elsevier DOI
0903
BibRef
Earlier:
Detection and segmentation of moving objects in highly dynamic scenes,
CVPR07(1-8).
IEEE DOI
0706
Motion detection, Segmentation, Mean shift clustering, Graph cuts
BibRef
Lee, S.[Soochahn],
Yun, I.D.[Il Dong],
Lee, S.U.[Sang Uk],
Robust bilayer video segmentation by adaptive propagation of global
shape and local appearance,
JVCIR(21), No. 7, October 2010, pp. 665-676.
Elsevier DOI
1003
Video segmentation, Shape prior, Local appearance, Adaptive local
refinement, Incremental shape set, Adaptive frame propagation;
Branch-and-mincut, MRF energy minimization
BibRef
Schoenemann, T.[Thomas],
Cremers, D.[Daniel],
A Coding-Cost Framework for Super-Resolution Motion Layer Decomposition,
IP(21), No. 3, March 2012, pp. 1097-1110.
IEEE DOI
1203
BibRef
Earlier:
High resolution motion layer decomposition using dual-space graph cuts,
CVPR08(1-7).
IEEE DOI
0806
BibRef
Earlier:
Near Real-Time Motion Segmentation Using Graph Cuts,
DAGM06(455-464).
Springer DOI
0610
BibRef
Mitzel, D.[Dennis],
Pock, T.[Thomas],
Schoenemann, T.[Thomas],
Cremers, D.[Daniel],
Video Super Resolution Using Duality Based TV-L1 Optical Flow,
DAGM09(432-441).
Springer DOI
0909
See also Efficient Dense Scene Flow from Sparse or Dense Stereo Data.
BibRef
Oh, S.C.[Sung-Chan],
Lee, H.J.[Hyug-Jae],
Kim, G.H.[Gyeong-Hwan],
Virtual Halo Effect Using Graph-Cut Based Video Segmentation,
IEICE(E96-D), No. 11, November 2013, pp. 2492-2495.
WWW Link.
1311
BibRef
Tian, Z.Q.[Zhi-Qiang],
Xue, J.R.[Jian-Ru],
Zheng, N.N.[Nan-Ning],
Lan, X.G.[Xu-Guang],
Li, C.[Ce],
3D spatio-temporal graph cuts for video objects segmentation,
ICIP11(2393-2396).
IEEE DOI
1201
BibRef
Ring, D.[Dan],
Kokaram, A.[Anil],
Feature-Cut: Video object segmentation through local feature
correspondences,
ObjectEvent09(617-624).
IEEE DOI
0910
BibRef
Guo, C.S.[Chun-Sheng],
Wang, P.[Pan],
Adaptive Graph-Cut Algorithm to Video Moving Objects Segmentation,
CISP09(1-5).
IEEE DOI
0910
BibRef
Wu, X.Y.[Xiao-Yu],
Yang, L.[Lei],
Yang, C.[Cheng],
Monocular Real-Time Foreground Cut Based on Multiple Cues,
CISP09(1-5).
IEEE DOI
0910
BibRef
Gong, M.L.[Ming-Lun],
Foreground segmentation of live videos using locally competing 1SVMs,
CVPR11(2105-2112).
IEEE DOI
1106
BibRef
Gong, M.L.[Ming-Lun],
Cheng, L.[Li],
Real-time foreground segmentation on GPUs using local online learning
and global graph cut optimization,
ICPR08(1-4).
IEEE DOI
0812
See also Incorporating estimated motion in real-time background subtraction.
BibRef
Sun, Y.[Yunda],
Yuan, B.Z.[Bao-Zong],
Miao, Z.J.[Zhen-Jiang],
Wan, C.K.[Cheng-Kai],
Better Foreground Segmentation for Static Cameras via New Energy Form
and Dynamic Graph-cut,
ICPR06(IV: 49-52).
IEEE DOI
0609
BibRef
Ahn, J.H.[Jung-Ho],
Kim, K.C.[Kil-Cheon],
Byun, H.R.[Hye-Ran],
Robust Object Segmentation Using Graph Cut with Object and Background
Seed Estimation,
ICPR06(II: 361-364).
IEEE DOI
0609
BibRef
And: A1, A3, Only:
Accurate Foreground Extraction Using Graph Cut with Trimap Estimation,
PSIVT06(1185-1194).
Springer DOI
0612
BibRef
Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Hough, Voting, Accumulation Methods for Moving Object Extraction .