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0304
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CVPR00(II: 142-149).
IEEE DOI
0005
Award, Longuet-Higgins.
BibRef
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WWW Link.
Award, CVPR. Feature histogram based representation.
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DAGM02(438 ff.).
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0303
BibRef
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Ramesh, V.[Visvanathan],
Mean Shift and Optimal Prediction for Efficient Object Tracking,
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0008
BibRef
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CamShift guided particle filter; Particle filter; CamShift; Visual
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0906
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1106
In multi-target tracking.
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1008
BibRef
Earlier: A2, A4, A3, Only:
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ECCV10(VI: 547-560).
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1009
graph theory
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1101
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1311
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1106
Adaptation models
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1009
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0806
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0408
Kernel density approximation technique based on the mean-shift
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0903
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Kernel-Based Bayesian Filtering for Object Tracking,
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0507
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0903
BibRef
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IEEE DOI
0510
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And:
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ICIP05(II: 442-445).
IEEE DOI
0512
BibRef
Earlier:
Object tracking by adaptive feature extraction,
ICIP04(III: 1501-1504).
IEEE DOI
0505
Visual tracking; Density-based fusion; Mean-shift; Component-based tracking
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Probabilistic Fusion Tracking Using Mixture Kernel-Based Bayesian
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0711
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0811
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Earlier: A1, A4, A3, Only:
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0806
BibRef
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Mean-shift blob tracking through scale space,
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0307
BibRef
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CVIU(113), No. 2, February 2009, pp. 273-290.
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0901
Simplified color correlogram (SCC); Kernel based tracking;
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BibRef
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0806
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ACCV09(I: 258-268).
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0909
BibRef
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0710
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0710
BibRef
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CVIU(113), No. 3, March 2009, pp. 345-352.
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0902
Award, CVIU, Most Cited. (2009-2011)
Object tracking; Color histogram; Mean shift; SIFT features;
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BibRef
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IEEE DOI
0911
BibRef
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0905
Mean-Shift; Multi-cue tracking; Adaptive integration
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CVIU(113), No. 4, April 2009, pp. 544-555.
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0903
Object representation; Color histogram; Tracking; Mean Shift; Particle Filter
BibRef
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Cavallaro, A.[Andrea],
Learning Scene Context for Multiple Object Tracking,
IP(18), No. 8, August 2009, pp. 1873-1884.
IEEE DOI
0907
BibRef
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Integrating Color and Shape-Texture Features for Adaptive Real-Time
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IP(17), No. 2, February 2008, pp. 235-240.
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0801
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1306
Shape priors; Image segmentation; Video segmentation;
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BibRef
Wang, J.Q.[Jun-Qiu],
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Cyber(44), No. 7, July 2014, pp. 1237-1248.
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1407
BibRef
Earlier:
Switching local and covariance matching for efficient object tracking,
ICPR08(1-4).
IEEE DOI
0812
BibRef
And:
Patch-based adaptive tracking using spatial and appearance information,
ICIP08(1564-1567).
IEEE DOI
0810
BibRef
Earlier:
Discriminative Mean Shift Tracking with Auxiliary Particles,
ACCV07(I: 576-585).
Springer DOI
0711
Histograms
BibRef
Li, S.X.[Shu-Xiao],
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Global visual tracking; Fast mean shift; Adaptive level; Kernel-based
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BibRef
Khan, Z.H.[Zulfiqar Hasan],
Gu, I.Y.H.[Irene Yu-Hua],
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Robust Visual Object Tracking Using Multi-Mode Anisotropic Mean Shift
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CirSysVideo(21), No. 1, January 2011, pp. 74-87.
IEEE DOI
1103
BibRef
Earlier:
Joint particle filters and multi-mode anisotropic mean shift for robust
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ICIP09(4077-4080).
IEEE DOI
0911
BibRef
Khan, Z.H.[Zulfiqar Hasan],
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Nonlinear Dynamic Model for Visual Object Tracking on Grassmann
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Cyber(43), No. 6, 2013, pp. 2005-2019.
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1312
BibRef
Earlier: A2, A1:
Grassmann manifold online learning and partial occlusion handling for
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ICPR12(1463-1466).
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1302
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And: A1, A2:
Tracking visual and infrared objects using joint Riemannian manifold
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IEEE DOI
1201
BibRef
And: A1, A2:
Bayesian online learning on Riemannian manifolds using a dual model
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ITCVPR11(1402-1409).
IEEE DOI
1201
BibRef
And: A1, A2:
Visual tracking and dynamic learning on the Grassmann manifold with
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ICIP11(1433-1436).
IEEE DOI
1201
Bayesian methods
BibRef
Khan, Z.H.[Zulfiqar Hasan],
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CVIU(125), No. 1, 2014, pp. 97-114.
Elsevier DOI
1406
Domain-shift object learning
BibRef
Haner, S.[Sebastian],
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Combining Foreground / Background Feature Points and Anisotropic Mean
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ICPR10(3488-3491).
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1008
BibRef
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Kernel-based object tracking using asymmetric kernels with adaptive
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MVA(22), No. 2, March 2011, pp. 255-268.
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1103
BibRef
Earlier:
Object Tracking by Asymmetric Kernel Mean Shift with Automatic Scale
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CVPR07(1-6).
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0706
BibRef
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A unique target representation and voting mechanism for visual
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ICIP17(410-414)
IEEE DOI
1803
BibRef
Earlier:
Efficient tracking with distinctive target colors and silhouette,
ICPR16(2728-2733)
IEEE DOI
1705
Color, Feature extraction, Robustness, Target tracking, Training,
Visualization, visual tracking, voting.
Computational modeling, Histograms, Image color analysis,
Mathematical model.
BibRef
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Adaptive mean-shift for automated multi object tracking,
IET-CV(6), No. 1, 2012, pp. 1-12.
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1201
BibRef
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Wu, C.,
Scale and orientation adaptive mean shift tracking,
IET-CV(6), No. 1, 2012, pp. 52-61.
DOI Link
1201
BibRef
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Zhang, L.,
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Robust mean-shift tracking with corrected background-weighted histogram,
IET-CV(6), No. 1, 2012, pp. 62-69.
DOI Link
1201
Award, IET CV Premium.
BibRef
Prisacariu, V.A.[Victor Adrian],
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PWP3D: Real-Time Segmentation and Tracking of 3D Objects,
IJCV(98), No. 3, July 2012, pp. 335-354.
WWW Link.
1202
BibRef
Earlier:
BMVC09(xx-yy).
PDF File.
0909
BibRef
And:
Shared shape spaces,
ICCV11(2587-2594).
IEEE DOI
1201
BibRef
And:
Nonlinear shape manifolds as shape priors in level set segmentation and
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CVPR11(2185-2192).
IEEE DOI
1106
BibRef
Ren, C.Y.H.[Carl Yu-Heng],
Prisacariu, V.A.[Victor A.],
Kähler, O.[Olaf],
Reid, I.D.[Ian D.],
Murray, D.W.[David W.],
Real-Time Tracking of Single and Multiple Objects from Depth-Colour
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IJCV(124), No. 1, August 2016, pp. 80-95.
Springer DOI
1707
BibRef
Earlier:
3D Tracking of Multiple Objects with Identical Appearance Using RGB-D
Input,
3DV14(47-54)
IEEE DOI
1503
Cameras
BibRef
Kähler, O.[Olaf],
Prisacariu, V.A.[Victor Adrian],
Murray, D.W.[David W.],
Real-Time Large-Scale Dense 3D Reconstruction with Loop Closure,
ECCV16(VIII: 500-516).
Springer DOI
1611
BibRef
Ren, C.Y.H.[Carl Yu-Heng],
Prisacariu, V.A.[Victor A.],
Murray, D.W.[David W.],
Reid, I.D.[Ian D.],
STAR3D:
Simultaneous Tracking and Reconstruction of 3D Objects Using RGB-D Data,
ICCV13(1561-1568)
IEEE DOI
1403
3D Reconstruction; 3D Tracking; Generative model
BibRef
Dame, A.[Amaury],
Prisacariu, V.A.[Victor A.],
Ren, C.Y.[Carl Y.],
Reid, I.D.[Ian D.],
Dense Reconstruction Using 3D Object Shape Priors,
CVPR13(1288-1295)
IEEE DOI
1309
Dense reconstruction; SLAM; shape prior
BibRef
Prisacariu, V.A.[Victor Adrian],
Segal, A.V.[Aleksandr V.],
Reid, I.D.[Ian D.],
Simultaneous Monocular 2D Segmentation, 3D Pose Recovery and 3D
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ACCV12(I:593-606).
Springer DOI
1304
BibRef
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Prisacariu, V.A.[Victor Adrian],
Reid, I.D.[Ian D.],
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IJCV(106), No. 3, February 2014, pp. 269-281.
WWW Link.
1402
BibRef
Earlier:
BMVC11(xx-yy).
HTML Version.
1110
BibRef
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Zhao, C.[Chuan],
Mean-shift Visual Tracking with NP-Windows Density Estimates,
BMVC10(xx-yy).
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1009
BibRef
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Reid, I.D.[Ian D.],
Target tracking using mean-shift and affine structure,
ICPR08(1-5).
IEEE DOI
0812
BibRef
Bousetouane, F.[Fouad],
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Improved mean shift integrating texture and color features for robust
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On the convergence of the mean shift algorithm in the one-dimensional
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Elsevier DOI
1306
Mean shift algorithm; Mode estimate sequence; Monotone
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BibRef
Wang, L.F.[Ling-Feng],
Yan, H.,
Wu, H.Y.[Huai-Yu],
Pan, C.H.[Chun-Hong],
Forward-Backward Mean-Shift for Visual Tracking With
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ITS(14), No. 3, 2013, pp. 1480-1489.
IEEE DOI
1309
Forward-backward mean shift (FBMS)
BibRef
Wang, L.F.[Ling-Feng],
Yan, H.,
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Visual Tracking Via Kernel Sparse Representation With Multikernel
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CirSysVideo(24), No. 7, July 2014, pp. 1132-1141.
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1407
Computational efficiency
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Wu, H.Y.[Huai-Yu],
Pan, C.H.[Chun-Hong],
Mean-Shift Object Tracking with a Novel Back-Projection Calculation
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ACCV09(I: 83-92).
Springer DOI
0909
BibRef
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MEAN-shift tracking algorithm with weight fusion strategy,
ICIP11(473-476).
IEEE DOI
1201
BibRef
Wen, J.J.[Jia-Jun],
Xu, Y.[Yong],
Chen, Y.[Yan],
He, L.W.[Li-Wen],
Recent Advance on Mean Shift Tracking: A Survey,
IJIG(13), No. 03, 2013, pp. 1350012.
DOI Link
1309
Survey, Mean Shift.
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An, X.,
Kim, J.,
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Optimal colour-based mean shift algorithm for tracking objects,
IET-CV(8), No. 3, June 2014, pp. 235-244.
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1407
BibRef
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Robust Scale-Adaptive Mean-Shift for Tracking,
PRL(49), No. 1, 2014, pp. 250-258.
Elsevier DOI
1410
BibRef
Earlier:
SCIA13(652-663).
Springer DOI
1311
Object tracking
BibRef
Chen, X.H.[Xiao-Hui],
Zhang, M.J.[Meng-Jiao],
Ruan, K.[Kai],
Xu, G.Z.[Guang-Zhu],
Sun, S.F.[Shui-Fa],
Gong, C.F.[Can-Feng],
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Lei, B.J.[Bang-Jun],
Improved mean shift target tracking based on self-organizing maps,
SIViP(8), No. S1, December 2014, pp. 103-112.
Springer DOI
1411
BibRef
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Dan, Z.P.[Zhi-Ping],
Lei, B.J.[Bang-Jun],
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Improved dual-mode compressive tracking integrating balanced colour and
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IET-CV(12), No. 8, December 2018, pp. 1200-1206.
DOI Link
1812
BibRef
Laguzet, F.[Florence],
Romero, A.[Andres],
Gouiffès, M.[Michèle],
Lacassagne, L.[Lionel],
Etiemble, D.[Daniel],
Color tracking with contextual switching:
Real-time implementation on CPU,
RealTimeIP(10), No. 2, June 2015, pp. 403-422.
Springer DOI
1506
mean-shift (MS) and covariance tracking (CT)
BibRef
Song, Y.[Yi],
Li, S.X.[Shu-Xiao],
Zhu, C.F.[Cheng-Fei],
Jiang, S.[Sheng],
Chang, H.X.[Hong-Xing],
Invariant foreground occupation ratio for scale adaptive mean shift
tracking,
IET-CV(9), No. 4, 2015, pp. 489-499.
DOI Link
1509
BibRef
And:
Erratum:
IET Computer Vision(10), No. 2, 2016, pp. 172-172.
DOI Link
1603
approximation theory
BibRef
Song, Y.[Yi],
Li, S.X.[Shu-Xiao],
Zhang, J.L.[Jing-Lan],
Chang, H.X.[Hong-Xing],
Scale Adaptive Tracking Using Mean Shift and Efficient Feature
Matching,
ICPR14(2233-2238)
IEEE DOI
1412
Feature extraction
BibRef
Song, Y.[Yi],
Li, S.X.[Shu-Xiao],
Chang, H.X.[Hong-Xing],
Scale Adaptive Mean Shift Tracking Based on Feature Point Matching,
ACPR13(220-224)
IEEE DOI
1408
affine transforms
BibRef
Varfolomieiev, A.,
Lysenko, O.,
An improved algorithm of median flow for visual object tracking and its
implementation on ARM platform,
RealTimeIP(11), No. 3, March 2016, pp. 527-534.
Springer DOI
1604
BibRef
Lu, R.T.[Rui-Tao],
Xu, W.Y.[Wan-Ying],
Zheng, Y.B.[Yong-Bin],
Huang, X.S.[Xin-Sheng],
Visual Tracking via Probabilistic Hypergraph Ranking,
CirSysVideo(27), No. 4, April 2017, pp. 866-879.
IEEE DOI
1704
Classification algorithms
BibRef
Shen, L.R.[Lu-Rong],
Huang, X.S.[Xin-Sheng],
Xu, W.Y.[Wan-Ying],
Zheng, Y.B.[Yong-Bin],
Robust Visual Tracking by Integrating Lucas-Kanade into Mean-Shift,
ICIG11(660-666).
IEEE DOI
1109
BibRef
Phadke, G.[Gargi],
Velmurugan, R.[Rajbabu],
Mean LBP and modified fuzzy C-means weighted hybrid feature for
illumination invariant mean-shift tracking,
SIViP(11), No. 4, May 2017, pp. 665-672.
WWW Link.
1704
BibRef
Medouakh, S.[Saadia],
Boumehraz, M.[Mohamed],
Terki, N.[Nadjiba],
Improved object tracking via joint color-LPQ texture histogram based
mean shift algorithm,
SIViP(12), No. 3, March 2018, pp. 583-590.
WWW Link.
1804
BibRef
Rowghanian, V.[Vahid],
Ansari-Asl, K.[Karim],
Object tracking by mean shift and radial basis function neural networks,
RealTimeIP(15), No. 4, December 2018, pp. 799-816.
WWW Link.
1812
BibRef
Topkaya, I.S.[Ibrahim Saygin],
Erdogan, H.[Hakan],
Using spatial overlap ratio of independent classifiers for likelihood
map fusion in mean-shift tracking,
SIViP(13), No. 1, February 2019, pp. 61-67.
WWW Link.
1901
BibRef
Liu, Y.,
Jing, X.,
Nie, J.,
Gao, H.,
Liu, J.,
Jiang, G.,
Context-Aware Three-Dimensional Mean-Shift With Occlusion Handling
for Robust Object Tracking in RGB-D Videos,
MultMed(21), No. 3, March 2019, pp. 664-677.
IEEE DOI
1903
approximation theory, image colour analysis, object tracking,
statistical distributions, stereo image processing,
point cloud
BibRef
Yamasaki, R.[Ryoya],
Tanaka, T.[Toshiyuki],
Properties of Mean Shift,
PAMI(42), No. 9, September 2020, pp. 2273-2286.
IEEE DOI
2008
For estimating modes of probability density functions.
Kernel, Probability density function, Convergence,
Clustering algorithms, Estimation, Bandwidth, Trajectory,
subspace constrained mean shift algorithm
BibRef
Yang, J.W.[Jia-Wei],
Rahardja, S.[Susanto],
Fränti, P.[Pasi],
Mean-shift outlier detection and filtering,
PR(115), 2021, pp. 107874.
Elsevier DOI
2104
Outlier detection, Anomaly detection, Mean-shift, Medoid-shift,
Clustering, Noise filtering, Outlier filtering
BibRef
Gao, X.[Xiang],
Zhu, L.J.[Ling-Jie],
Fan, B.[Bin],
Liu, H.M.[Hong-Min],
Shen, S.H.[Shu-Han],
Incremental Translation Averaging,
CirSysVideo(32), No. 11, November 2022, pp. 7783-7795.
IEEE DOI
2211
Cameras, Estimation, Robustness, Pipelines, Cost function,
Parameter estimation, Barium, Translation averaging, simplicity and efficiency
BibRef
Manam, L.[Lalit],
Govindu, V.M.[Venu Madhav],
Correspondence Reweighted Translation Averaging,
ECCV22(XXXIII:56-72).
Springer DOI
2211
BibRef
Jang, J.[Jennifer],
Jiang, H.[Heinrich],
MeanShift++: Extremely Fast Mode-Seeking With Applications to
Segmentation and Object Tracking,
CVPR21(4100-4111)
IEEE DOI
2111
Measurement, Image segmentation, Runtime,
Machine learning algorithms, Frequency modulation, Clustering algorithms
BibRef
Ajmal, A.,
Hollitt, C.,
Frean, M.,
Active shift attention based object tracking system,
IVCNZ17(1-5)
IEEE DOI
1902
image sequences, Kalman filters, mean square error methods,
object detection, object tracking, multiple objects,
Covariance matrices
BibRef
Duncan, K.R.,
Stewart, R.,
Michaelson, G.,
Parallel Mean Shift Accuracy and Performance Trade-Offs,
ICIP18(2197-2201)
IEEE DOI
1809
Image segmentation, Merging,
Clustering algorithms, Indexes, Probabilistic logic,
parallel processing
BibRef
Cui, H.,
Shen, S.,
Hu, Z.,
Robust global translation averaging with feature tracks,
ICPR16(3727-3732)
IEEE DOI
1705
Cameras, Estimation, Geometry, Image edge detection,
Image reconstruction, Noise measurement, Optimization
BibRef
Iraei, I.[Iman],
Faez, K.[Karim],
Object tracking with occlusion handling using mean shift, Kalman
filter and Edge Histogram,
IPRIA15(1-6)
IEEE DOI
1603
Kalman filters
BibRef
Hedayati, M.,
Cree, M.J.,
Scott, J.B.,
Effect of contextual information on object tracking,
IVCNZ17(1-6)
IEEE DOI
1902
BibRef
Earlier:
Combination of Mean Shift of Colour Signature and Optical Flow for
Tracking During Foreground and Background Occlusion,
PSIVT15(87-98).
Springer DOI
1602
feature extraction, image motion analysis, image representation,
image sequences, object tracking, video signal processing,
occlusion
BibRef
Sliti, O.[Oumaima],
Hamam, H.[Habib],
Benzarti, F.[Faouzi],
Amiri, H.[Hamid],
A More Robust Mean Shift Tracker Using Joint Monogenic Signal
Analysis and Color Histogram,
ICPR14(2453-2458)
IEEE DOI
1412
Color
BibRef
Phadke, G.,
Velmurugan, R.,
Improved mean shift for multi-target tracking,
PETS13(37-44)
IEEE DOI
1411
Kalman filters
BibRef
Sawhney, R.[Rahul],
Christensen, H.I.[Henrik I.],
Bradski, G.[Gary],
Anisotropic Agglomerative Adaptive Mean-Shift,
BMVC14(xx-yy).
HTML Version.
1410
BibRef
Zhang, Z.[Zhe],
Wong, K.H.[Kin Hong],
Pyramid-Based Visual Tracking Using Sparsity Represented Mean
Transform,
CVPR14(1226-1233)
IEEE DOI
1409
BibRef
Okade, M.,
Biswas, P.K.,
Mean shift clustering based outlier removal for global motion
estimation,
NCVPRIPG13(1-4)
IEEE DOI
1408
cameras
BibRef
Tomiyasu, F.,
Hirayama, T.,
Mase, K.,
Wide-Range Feature Point Tracking with Corresponding Point Search and
Accurate Feature Point Tracking with Mean-Shift,
ACPR13(907-911)
IEEE DOI
1408
feature extraction
BibRef
Sojka, E.[Eduard],
Šurkala, M.[Milan],
Gaura, J.[Jan],
Mean Shift with Flatness Constraints,
SCIA13(107-118).
Springer DOI
1311
BibRef
Suárez, Y.G.[Yasel Garcés],
Torres, E.[Esley],
Pereira, O.[Osvaldo],
Pérez, C.[Claudia],
Rogríguez, R.[Roberto],
Stopping Criterion for the Mean Shift Iterative Algorithm,
CIARP13(I:383-390).
Springer DOI
1311
BibRef
Phadke, G.,
Velmurgan, R.,
Illumination invariant Mean-shift tracking,
WACV13(407-412).
IEEE DOI
1303
BibRef
Tang, D.[Da],
Zhang, Y.J.[Yu-Jin],
Combining Mean-Shift and Particle Filter for Object Tracking,
ICIG11(771-776).
IEEE DOI
1109
BibRef
di Caterina, G.[Gaetano],
Soraghan, J.J.[John J.],
An improved Mean Shift tracker with fast failure recovery strategy
after complete occlusion,
AVSBS11(130-135).
IEEE DOI
1111
BibRef
Šurkala, M.[Milan],
Fusek, R.[Radovan],
Holuša, M.[Michael],
Sojka, E.[Eduard],
Hierarchical Fast Mean-Shift Segmentation in Depth Images,
ACIVS16(441-452).
Springer DOI
1611
BibRef
Šurkala, M.[Milan],
Mozdren, K.[Karel],
Fusek, R.[Radovan],
Sojka, E.[Eduard],
Hierarchical Layered Mean Shift Methods,
ACIVS13(538-545).
Springer DOI
1311
BibRef
And:
Layered Mean Shift Methods,
SSVM13(465-476).
Springer DOI
1305
BibRef
Earlier:
Hierarchical evolving mean-shift,
ICIP12(1593-1596).
IEEE DOI
1302
BibRef
Earlier:
Hierarchical Blurring Mean-Shift,
ACIVS11(228-238).
Springer DOI
1108
BibRef
Bai, K.[Kejia],
Particle filter tracking with Mean Shift and joint probability data
association,
IASP10(607-612).
IEEE DOI
1004
BibRef
Sojka, E.[Eduard],
Gaura, J.[Jan],
Fabián, T.[Tomáš],
Krumnikl, M.[Michal],
Fast Mean Shift Algorithm Based on Discretisation and Interpolation,
ACIVS10(I: 402-413).
Springer DOI
1012
BibRef
Sojka, E.[Eduard],
Gaura, J.[Jan],
Šrubar, Š.[Štepán],
Fabián, T.[Tomáš],
Krumnikl, M.[Michal],
Blurring Mean-Shift with a Restricted Data-Set Modification for
Applications in Image Processing,
ISVC10(III: 310-319).
Springer DOI
1011
BibRef
Gouiffes, M.[Michele],
Laguzet, F.[Florence],
Lacassagne, L.[Lionel],
Projection-histograms for mean-shift tracking,
ICIP10(4617-4620).
IEEE DOI
1009
BibRef
Khan, I.R.[Ishtiaq Rasool],
Farbiz, F.[Farzam],
A back projection scheme for accurate mean shift based tracking,
ICIP10(33-36).
IEEE DOI
1009
BibRef
Gouiffes, M.[Michele],
Laguzet, F.[Florence],
Lacassagne, L.[Lionel],
Color Connectedness Degree for Mean-Shift Tracking,
ICPR10(4561-4564).
IEEE DOI
1008
BibRef
Yoon, J.W.[Ji Won],
Wilson, S.P.[Simon P.],
Improved Mean Shift Algorithm with Heterogeneous Node Weights,
ICPR10(4222-4225).
IEEE DOI
1008
BibRef
Zhuang, D.Y.[Da-Yuan],
Ma, X.H.[Xiao-Hu],
Xu, Y.L.[Yun-Long],
Real-time tracking algorithm based on improved Mean Shift and Kalman
filter,
IASP10(100-103).
IEEE DOI
1004
BibRef
Aslam, S.[Salman],
Bobick, A.F.[Aaron F.],
Barnes, C.[Christopher],
Sezer, O.[Osman],
Better computer vision under video compression, an example using mean
shift tracking,
ICIP09(3629-3632).
IEEE DOI
0911
BibRef
Zhou, B.[Bin],
Wang, J.Z.[Jun-Zheng],
Shen, W.[Wei],
Object tracking based on multi-bandwidth mean shift with convergence
acceleration,
IASP10(613-619).
IEEE DOI
1004
BibRef
Zhou, B.[Bin],
Wang, J.Z.[Jun-Zheng],
Li, J.[Jing],
Shen, W.[Wei],
Object Tracking with Mean Shift and Model Prediction,
CISP09(1-5).
IEEE DOI
0910
BibRef
Li, B.[Bo],
Zeng, Z.Y.[Zhi-Yuan],
Wu, Z.R.[Zhong-Ru],
Multi-Object Tracking Based on Improved Mean-Shift Algorithm,
CISP09(1-5).
IEEE DOI
0910
BibRef
Lou, Z.Y.[Zhong-Yu],
Jiang, G.[Guang],
Wu, C.K.[Cheng-Ke],
Mean-Shift Tracking of Variable Kernel Based on Projective Geometry,
CISP09(1-4).
IEEE DOI
0910
BibRef
Tung, F.[Frederick],
Zelek, J.S.[John S.],
Clausi, D.A.[David A.],
Efficient Target Recovery Using STAGE for Mean-shift Tracking,
CRV09(16-22).
IEEE DOI
0905
BibRef
Li, P.H.[Pei-Hua],
Sun, Q.[Qi],
Tensor-based covariance matrices for object tracking,
VS11(1681-1688).
IEEE DOI
1201
BibRef
Li, P.H.[Pei-Hua],
Xiao, L.J.[Li-Juan],
Mean Shift Parallel Tracking on GPU,
IbPRIA09(120-127).
Springer DOI
0906
BibRef
Earlier: A2, A1:
Improvement on Mean Shift based tracking using second-order information,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Yi, K.M.[Kwang Moo],
Kim, S.W.[Soo Wan],
Choi, J.Y.[Jin Young],
Orientation and Scale Invariant Kernel-Based Object Tracking with
Probabilistic Emphasizing,
ACCV09(II: 130-139).
Springer DOI
0909
BibRef
Yi, K.M.[Kwang Moo],
Ahn, H.S.[Ho Seok],
Choi, J.Y.[Jin Young],
Orientation and scale invariant mean shift using object mask-based
kernel,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Li, Z.D.[Zhi-Dong],
Chen, J.[Jing],
Schraudolph, N.N.[Nicol N.],
An improved mean-shift tracker with kernel prediction and scale
optimisation targeting for low-frame-rate video tracking,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Shi, Y.[Ying],
Liu, H.[Hong],
Liu, Y.[Yi],
Zha, H.B.[Hong-Bin],
Adaptive feature-spatial representation for Mean-shift tracker,
ICIP08(2012-2015).
IEEE DOI
0810
BibRef
Li, G.R.[Guo-Rong],
Liang, D.W.[Da-Wei],
Huang, Q.M.[Qing-Ming],
Jiang, S.Q.[Shu-Qiang],
Gao, W.[Wen],
Object tracking using incremental 2D-LDA learning and Bayes inference,
ICIP08(1568-1571).
IEEE DOI
0810
BibRef
Liang, D.W.[Da-Wei],
Huang, Q.M.[Qing-Ming],
Jiang, S.Q.[Shu-Qiang],
Yao, H.X.[Hong-Xun],
Gao, W.[Wen],
Mean-Shift Blob Tracking with Adaptive Feature Selection and Scale
Adaptation,
ICIP07(III: 369-372).
IEEE DOI
0709
BibRef
Caulfield, D.[Darren],
Dawson-Howe, K.M.[Kenneth M.],
Evaluation of Multi-part Models for Mean-Shift Tracking,
IMVIP08(77-82).
IEEE DOI
0809
BibRef
Pridmore, T.P.,
Naeem, A.,
Mills, S.,
Managing Particle Spread via Hybrid Particle Filter/Kernel Mean Shift
Tracking,
BMVC07(xx-yy).
PDF File.
0709
BibRef
Draréni, J.[Jamil],
Roy, S.[Sébastien],
A Simple Oriented Mean-Shift Algorithm for Tracking,
ICIAR07(558-568).
Springer DOI
0708
BibRef
Leung, A.P.,
Gong, S.,
Mean-Shift Tracking with Random Sampling,
BMVC06(II:729).
PDF File.
0609
BibRef
Deguchi, K.,
Kawanaka, O.,
Okatani, T.,
Object tracking by the mean-shift of regional color distribution
combined with the particle-filter algorithm,
ICPR04(III: 506-509).
IEEE DOI
0409
BibRef
Abrantes, A.J.,
Marques, J.S.,
The mean shift algorithm and the unified framework,
ICPR04(I: 244-247).
IEEE DOI
0409
BibRef
Abrantes, A.J.[Arnaldo J.],
Marques, J.S.[Jorge S.],
Shape Tracking Using Centroid-Based Methods,
EMMCVPR01(576-591).
Springer DOI
0205
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Target Tracking, Active, Camera Following, Real Time Issues, Hardware .