16.6.2.10 Mean-Shift Tracking Techniques

Chapter Contents (Back)
Target Tracking. Mean-Shift Tracking.

Comaniciu, D.[Dorin], Ramesh, V.[Visvanathan], Meer, P.[Peter],
Kernel-based object tracking,
PAMI(25), No. 5, May 2003, pp. 564-577.
IEEE Abstract. 0304
BibRef
Earlier:
Real-Time Tracking of Non-Rigid Objects using Mean Shift,
CVPR00(II: 142-149).
IEEE DOI 0005
Award, Longuet-Higgins. BibRef
And: A1, A2 only: US_Patent6,590,999, July 8, 2003.
WWW Link. Award, CVPR. Feature histogram based representation. BibRef

Comaniciu, D.,
Bayesian Kernel Tracking,
DAGM02(438 ff.).
Springer DOI 0303
BibRef

Comaniciu, D.[Dorin], Ramesh, V.[Visvanathan],
Mean Shift and Optimal Prediction for Efficient Object Tracking,
ICIP00(Vol III: 70-73).
IEEE DOI 0008
BibRef

Zhou, X.S., Comaniciu, D., Xie, B., Cruceanu, R., Gupta, A.,
A unified framework for uncertainty propagation in automatic shape tracking,
CVPR04(I: 872-879).
IEEE DOI 0408
BibRef

Wang, Z.W.[Zhao-Wen], Yang, X.K.[Xiao-Kang], Xu, Y.[Yi], Yu, S.Y.[Song-Yu],
CamShift guided particle filter for visual tracking,
PRL(30), No. 4, 1 March 2009, pp. 407-413.
Elsevier DOI 0903
CamShift guided particle filter; Particle filter; CamShift; Visual tracking algorithm BibRef

Medrano, C.[Carlos], Herrero-Jaraba, J.E.[J. Elias], Martinez-del-Rincon, J.[Jesus], Orrite-Urunuela, C.[Carlos],
Mean field approach for tracking similar objects,
CVIU(113), No. 8, August 2009, pp. 907-920.
Elsevier DOI 0906
BibRef
Earlier: A3, A4, A2, Only:
An efficient particle filter for color-based tracking in complex scenes,
AVSBS07(176-181).
IEEE DOI 0709
Multi-target tracking; Mean field; Particle filter; Kalman filter BibRef

Medrano, C.[Carlos], Igual, R.[Raúl], Orrite, C.[Carlos], Plaza, I.[Inmaculada],
Occlusion Management in Sequential Mean Field Monte Carlo Methods,
IbPRIA11(444-451).
Springer DOI 1106
In multi-target tracking. BibRef

Medrano, C., Igual, R., Martinez-del-Rincon, J.[Jesus], Orrite-Urunuela, C.[Carlos],
Multi-target tracking with occlusion management in a mean field framework,
VS08(xx-yy). 0810
BibRef

Martinez-del-Rincon, J.[Jesus], Makris, D.[Dimitrios], Orrite-Urunuela, C.[Carlos], Nebel, J.C.[Jean-Christophe],
Tracking Human Position and Lower Body Parts Using Kalman and Particle Filters Constrained by Human Biomechanics,
SMC-B(41), No. 1, February 2011, pp. 26-37.
IEEE DOI 1102
BibRef
Earlier: A1, A4, A2, A3:
Tracking Human Body Parts Using Particle Filters Constrained by Human Biomechanics,
BMVC08(xx-yy).
PDF File. 0809
BibRef

Martínez del Rincón, J.[Jesús], Lewandowski, M.[Michal], Nebel, J.C.[Jean-Christophe], Makris, D.[Dimitrios],
Generalized Laplacian Eigenmaps for Modeling and Tracking Human Motions,
Cyber(44), No. 9, September 2014, pp. 1646-1660.
IEEE DOI 1410
BibRef
Earlier: A2, A1, A4, A2:
Temporal Extension of Laplacian Eigenmaps for Unsupervised Dimensionality Reduction of Time Series,
ICPR10(161-164).
IEEE DOI 1008
BibRef
Earlier: A2, A4, A3, Only:
View and Style-Independent Action Manifolds for Human Activity Recognition,
ECCV10(VI: 547-560).
Springer DOI 1009
graph theory BibRef

Martínez del Rincón, J.[Jesús], Nebel, J.C.[Jean-Christophe], Makris, D.[Dimitrios],
Graph-based Particle Filter for Human Tracking with Stylistic Variations,
BMVC11(xx-yy).
HTML Version. 1110
Award, BMVC, Best Poster. BibRef

Martinez-del-Rincon, J.[Jesus], Orrite-Urunuela, C.[Carlos], Medrano, C.[Carlos],
Rao-Blackwellised particle filter for colour-based tracking,
PRL(32), No. 2, 15 January 2011, pp. 210-220.
Elsevier DOI 1101
Rao-Blackwellised particle filter; Colour updating; Tracking; PDA Kalman filter; Kernel density estimation BibRef

Martínez del Rincón, J.[Jesús], Santofimia, M.J.[Maria J.], Nebel, J.C.[Jean-Christophe],
Common-sense reasoning for human action recognition,
PRL(34), No. 15, 2013, pp. 1849-1860.
Elsevier DOI 1309
Common sense BibRef

Liu, B.Y.[Bai-Yang], Huang, J.Z.[Jun-Zhou], Kulikowski, C.[Casimir], Yang, L.[Lin],
Robust Visual Tracking Using Local Sparse Appearance Model and K-Selection,
PAMI(35), No. 12, 2013, pp. 2968-2981.
IEEE DOI 1311
BibRef
Earlier: A1, A2, A4, A3:
Robust tracking using local sparse appearance model and K-selection,
CVPR11(1313-1320).
IEEE DOI 1106
Adaptation models BibRef

Liu, B.Y.[Bai-Yang], Yang, L.[Lin], Huang, J.Z.[Jun-Zhou], Meer, P.[Peter], Gong, L.G.[Lei-Guang], Kulikowski, C.[Casimir],
Robust and Fast Collaborative Tracking with Two Stage Sparse Optimization,
ECCV10(IV: 624-637).
Springer DOI 1009
BibRef

Han, B.H.[Bo-Hyung], Comaniciu, D.[Dorin], Zhu, Y.[Ying], Davis, L.S.[Larry S.],
Sequential Kernel Density Approximation and Its Application to Real-Time Visual Tracking,
PAMI(30), No. 7, July 2008, pp. 1186-1197.
IEEE DOI 0806
BibRef
Earlier: A1, A2, A3, A4:
Incremental density approximation and kernel-based Bayesian filtering for object tracking,
CVPR04(I: 638-644).
IEEE DOI 0408
Kernel density approximation technique based on the mean-shift mode finding algorithm BibRef

Han, B.H.[Bo-Hyung], Zhu, Y.[Ying], Comaniciu, D.[Dorin], Davis, L.S.[Larry S.],
Visual Tracking by Continuous Density Propagation in Sequential Bayesian Filtering Framework,
PAMI(31), No. 5, May 2009, pp. 919-930.
IEEE DOI 0903
BibRef
Earlier:
Kernel-Based Bayesian Filtering for Object Tracking,
CVPR05(I: 227-234).
IEEE DOI 0507
Particle filtering in tracking. BibRef

Han, B.H.[Bo-Hyung], Davis, L.S.[Larry S.],
Probabilistic fusion-based parameter estimation for visual tracking,
CVIU(113), No. 4, April 2009, pp. 435-445.
Elsevier DOI 0903
BibRef
Earlier:
On-Line Density-Based Appearance Modeling for Object Tracking,
ICCV05(II: 1492-1499).
IEEE DOI 0510
BibRef
And:
Robust Observations for Object Tracking,
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 BibRef

Han, B.H.[Bo-Hyung], Joo, S.W.[Seong-Wook], Davis, L.S.[Larry S.],
Multi-Camera Tracking with Adaptive Resource Allocation,
IJCV(91), No. 1, January 2011, pp. 45-58.
WWW Link. 1101
BibRef
Earlier:
Probabilistic Fusion Tracking Using Mixture Kernel-Based Bayesian Filtering,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Yang, C.J.[Chang-Jiang], Duraiswami, R.[Ramani], Davis, L.S.[Larry S.],
Fast Multiple Object Tracking via a Hierarchical Particle Filter,
ICCV05(I: 212-219).
IEEE DOI 0510
Color and edge orientation. Coarse-to-fine matching. BibRef

Yang, C.J.[Chang-Jiang], Duraiswami, R.[Ramani], Davis, L.S.[Larry S.],
Efficient Mean-Shift Tracking via a New Similarity Measure,
CVPR05(I: 176-183).
IEEE DOI 0507
Alternate similarity measure for tracking. BibRef

Li, P.,
An Adaptive Binning Color Model for Mean Shift Tracking,
CirSysVideo(18), No. 9, September 2008, pp. 1293-1299.
IEEE DOI 0810
BibRef

Jeyakar, J.[Jaideep], Babu, R.V.[R. Venkatesh], Ramakrishnan, K.R.,
Robust object tracking with background-weighted local kernels,
CVIU(112), No. 3, December 2008, pp. 296-309.
Elsevier DOI 0711
BibRef
Earlier:
Robust Object Tracking using Local Kernels and Background Information,
ICIP07(V: 49-52).
IEEE DOI 0709
Mean shift; Object tracking; Kernel tracking BibRef

Hu, J.S.[Jwu-Sheng], Juan, C.W.[Chung-Wei], Wang, J.J.[Jyun-Ji],
A spatial-color mean-shift object tracking algorithm with scale and orientation estimation,
PRL(29), No. 16, 1 December 2008, pp. 2165-2173.
Elsevier DOI 0811
Mean-shift; Object tracking; Principle component analysis; Object deformation BibRef

Park, M.W.[Min-Woo], Brocklehurst, K.[Kyle], Collins, R.T.[Robert T.], Liu, Y.X.[Yan-Xi],
Deformed Lattice Detection in Real-World Images Using Mean-Shift Belief Propagation,
PAMI(31), No. 10, October 2009, pp. 1804-1816.
IEEE DOI 0909
BibRef
Earlier: A1, A3, A4, Only:
Deformed Lattice Discovery Via Efficient Mean-Shift Belief Propagation,
ECCV08(II: 474-485).
Springer DOI 0810
BibRef
Earlier: A1, A4, A3, Only:
Efficient mean shift belief propagation for vision tracking,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Park, M.W.[Min-Woo], Kashyap, S.[Somesh], Collins, R.T.[Robert T.], Liu, Y.X.[Yan-Xi],
Data driven mean-shift belief propagation for non-gaussian MRFs,
CVPR10(3547-3554).
IEEE DOI 1006
BibRef

Collins, R.T.,
Mean-shift blob tracking through scale space,
CVPR03(II: 234-240).
IEEE DOI 0307
BibRef

Zhao, Q.[Qi], Tao, H.[Hai],
A motion observable representation using color correlogram and its applications to tracking,
CVIU(113), No. 2, February 2009, pp. 273-290.
Elsevier DOI 0901
Simplified color correlogram (SCC); Kernel based tracking; Optimal feature selection BibRef

Tang, F.[Feng], Harville, M.[Michael], Tao, H.[Hai], Robinson, I.N.[Ian N.],
Fusion of local appearance with stereo depth for object tracking,
S3D08(1-8).
IEEE DOI 0806
BibRef

Zhao, Q.[Qi], Yang, Z.[Zhi], Tao, H.[Hai], Liu, W.T.[Wen-Tai],
Evolving Mean Shift with Adaptive Bandwidth: A Fast and Noise Robust Approach,
ACCV09(I: 258-268).
Springer DOI 0909
BibRef

Tang, F.[Feng], Brennan, S.[Shane], Zhao, Q.[Qi], Tao, H.[Hai],
Co-Tracking Using Semi-Supervised Support Vector Machines,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Zhao, Q.[Qi], Brennan, S.[Shane], Tao, H.[Hai],
Differential EMD Tracking,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Zhou, H.Y.[Hui-Yu], Yuan, Y.[Yuan], Shi, C.M.[Chun-Mei],
Object tracking using SIFT features and mean shift,
CVIU(113), No. 3, March 2009, pp. 345-352.
Elsevier DOI 0902
Award, CVIU, Most Cited. (2009-2011) Object tracking; Color histogram; Mean shift; SIFT features; Expectation-maximization BibRef

Zhou, H.Y.[Hui-Yu], Tao, D.C.[Da-Cheng], Yuan, Y.[Yuan], Li, X.L.[Xue-Long],
Object trajectory clustering via tensor analysis,
ICIP09(1945-1948).
IEEE DOI 0911
BibRef

Liu, H.[Hong], Yu, Z.[Ze], Zha, H.B.[Hong-Bin], Zou, Y.X.[Yue-Xian], Zhang, L.[Lin],
Robust human tracking based on multi-cue integration and mean-shift,
PRL(30), No. 9, 1 July 2009, pp. 827-837.
Elsevier DOI 0905
Mean-Shift; Multi-cue tracking; Adaptive integration BibRef

Liu, H.[Hong], Zhang, L.[Lin], Yu, Z.[Ze], Zha, H.B.[Hong-Bin], Shi, Y.[Ying],
Collaborative Mean Shift Tracking Based on Multi-Cue Integration and Auxiliary Objects,
ICIP07(III: 217-220).
IEEE DOI 0709
BibRef

Maggio, E.[Emilio], Cavallaro, A.[Andrea],
Accurate appearance-based Bayesian tracking for maneuvering targets,
CVIU(113), No. 4, April 2009, pp. 544-555.
Elsevier DOI 0903
Object representation; Color histogram; Tracking; Mean Shift; Particle Filter BibRef

Maggio, E.[Emilio], Cavallaro, A.[Andrea],
Learning Scene Context for Multiple Object Tracking,
IP(18), No. 8, August 2009, pp. 1873-1884.
IEEE DOI 0907
BibRef

Wang, J.Q.[Jun-Qiu], Yagi, Y.S.[Yasu-Shi],
Integrating Color and Shape-Texture Features for Adaptive Real-Time Object Tracking,
IP(17), No. 2, February 2008, pp. 235-240.
IEEE DOI 0801

See also Shadow extraction and application in pedestrian detection. BibRef

Wang, J.Q.[Jun-Qiu], Yagi, Y.S.[Yasu-Shi],
Shape priors extraction and application for geodesic distance transforms in images and videos,
PRL(34), No. 12, 1 September 2013, pp. 1386-1393.
Elsevier DOI 1306
Shape priors; Image segmentation; Video segmentation; Geodesic distance transform BibRef

Wang, J.Q.[Jun-Qiu], Yagi, Y.S.[Yasu-Shi],
Many-to-Many Superpixel Matching for Robust Tracking,
Cyber(44), No. 7, July 2014, pp. 1237-1248.
IEEE DOI 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], Chang, H.X.[Hong-Xing], Zhu, C.F.[Cheng-Fei],
Adaptive pyramid mean shift for global real-time visual tracking,
IVC(28), No. 3, March 2010, pp. 424-437.
Elsevier DOI 1001
Global visual tracking; Fast mean shift; Adaptive level; Kernel-based tracking; Tracking and pointing subsystem BibRef

Khan, Z.H.[Zulfiqar Hasan], Gu, I.Y.H.[Irene Yu-Hua], Backhouse, A.G.[Andrew G.],
Robust Visual Object Tracking Using Multi-Mode Anisotropic Mean Shift and Particle Filters,
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 tracking of video objects with partitioned areas,
ICIP09(4077-4080).
IEEE DOI 0911
BibRef

Khan, Z.H.[Zulfiqar Hasan], Gu, I.Y.H.[Irene Yu-Hua],
Nonlinear Dynamic Model for Visual Object Tracking on Grassmann Manifolds With Partial Occlusion Handling,
Cyber(43), No. 6, 2013, pp. 2005-2019.
IEEE DOI 1312
BibRef
Earlier: A2, A1:
Grassmann manifold online learning and partial occlusion handling for visual object tracking under Bayesian formulation,
ICPR12(1463-1466).
WWW Link. 1302
BibRef
And: A1, A2:
Tracking visual and infrared objects using joint Riemannian manifold appearance and affine shape modeling,
VS11(1847-1854).
IEEE DOI 1201
BibRef
And: A1, A2:
Bayesian online learning on Riemannian manifolds using a dual model with applications to video object tracking,
ITCVPR11(1402-1409).
IEEE DOI 1201
BibRef
And: A1, A2:
Visual tracking and dynamic learning on the Grassmann manifold with inference from a Bayesian framework and state space models,
ICIP11(1433-1436).
IEEE DOI 1201
Bayesian methods BibRef

Khan, Z.H.[Zulfiqar Hasan], Gu, I.Y.H.[Irene Yu-Hua],
Online domain-shift learning and object tracking based on nonlinear dynamic models and particle filters on Riemannian manifolds,
CVIU(125), No. 1, 2014, pp. 97-114.
Elsevier DOI 1406
Domain-shift object learning BibRef

Haner, S.[Sebastian], Gu, I.Y.H.[Irene Yu-Hua],
Combining Foreground / Background Feature Points and Anisotropic Mean Shift For Enhanced Visual Object Tracking,
ICPR10(3488-3491).
IEEE DOI 1008
BibRef

Yilmaz, A.[Alper],
Kernel-based object tracking using asymmetric kernels with adaptive scale and orientation selection,
MVA(22), No. 2, March 2011, pp. 255-268.
WWW Link. 1103
BibRef
Earlier:
Object Tracking by Asymmetric Kernel Mean Shift with Automatic Scale and Orientation Selection,
CVPR07(1-6).
IEEE DOI 0706
BibRef

Xiao, C.L.[Chang-Lin], Yilmaz, A.[Alper],
A unique target representation and voting mechanism for visual tracking,
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

Beyan, C., Temizel, A.,
Adaptive mean-shift for automated multi object tracking,
IET-CV(6), No. 1, 2012, pp. 1-12.
DOI Link 1201
BibRef

Ning, J., Zhang, L., Zhang, D., Wu, C.,
Scale and orientation adaptive mean shift tracking,
IET-CV(6), No. 1, 2012, pp. 52-61.
DOI Link 1201
BibRef

Ning, J., Zhang, L., Zhang, D., Wu, C.,
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], Reid, I.D.[Ian D.],
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 tracking,
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 Imagery Using 3D Signed Distance Functions,
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 Reconstruction,
ACCV12(I:593-606).
Springer DOI 1304
BibRef

Ren, C.Y.H.[Carl Yu-Heng], Prisacariu, V.A.[Victor Adrian], Reid, I.D.[Ian D.],
Regressing Local to Global Shape Properties for Online Segmentation and Tracking,
IJCV(106), No. 3, February 2014, pp. 269-281.
WWW Link. 1402
BibRef
Earlier: BMVC11(xx-yy).
HTML Version. 1110
BibRef

Reid, I.D.[Ian D.], Zhao, C.[Chuan],
Mean-shift Visual Tracking with NP-Windows Density Estimates,
BMVC10(xx-yy).
HTML Version. 1009
BibRef

Zhao, C.[Chuan], Knight, A.[Andrew], Reid, I.D.[Ian D.],
Target tracking using mean-shift and affine structure,
ICPR08(1-5).
IEEE DOI 0812
BibRef

Bousetouane, F.[Fouad], Dib, L.[Lynda], Snoussi, H.[Hichem],
Improved mean shift integrating texture and color features for robust real time object tracking,
VC(29), No. 3, March 2013, pp. 155-170.
WWW Link. 1303
BibRef

Ghassabeh, Y.A.[Youness Aliyari],
On the convergence of the mean shift algorithm in the one-dimensional space,
PRL(34), No. 12, 1 September 2013, pp. 1423-1427.
Elsevier DOI 1306
Mean shift algorithm; Mode estimate sequence; Monotone sequence; Kernel function; Convex function; Convergence 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 Local-Background-Weighted Histogram,
ITS(14), No. 3, 2013, pp. 1480-1489.
IEEE DOI 1309
Forward-backward mean shift (FBMS) BibRef

Wang, L.F.[Ling-Feng], Yan, H., Lv, K., Pan, C.H.[Chun-Hong],
Visual Tracking Via Kernel Sparse Representation With Multikernel Fusion,
CirSysVideo(24), No. 7, July 2014, pp. 1132-1141.
IEEE DOI 1407
Computational efficiency BibRef

Wang, L.F.[Ling-Feng], Wu, H.Y.[Huai-Yu], Pan, C.H.[Chun-Hong],
Mean-Shift Object Tracking with a Novel Back-Projection Calculation Method,
ACCV09(I: 83-92).
Springer DOI 0909
BibRef

Wang, L.F.[Ling-Feng], Pan, C.H.[Chun-Hong], Xiang, S.M.[Shi-Ming],
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. BibRef

An, X., Kim, J., Han, Y.,
Optimal colour-based mean shift algorithm for tracking objects,
IET-CV(8), No. 3, June 2014, pp. 235-244.
DOI Link 1407
BibRef

Vojir, T.[Tomas], Noskova, J.[Jana], Matas, J.G.[Jiri G.],
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], Min, J.B.[Jiang-Bo], 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

Sun, S.F.[Shui-Fa], Liu, S.C.[Shi-Chao], Kang, S.W.[Shi-Wei], Xia, C.[Chong], Dan, Z.P.[Zhi-Ping], Lei, B.J.[Bang-Jun], Wu, Y.R.[Yi-Rong],
Improved dual-mode compressive tracking integrating balanced colour and texture features,
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


Navaneet, K.L., Koohpayegani, S.A.[Soroush Abbasi], Tejankar, A.[Ajinkya], Pourahmadi, K.[Kossar], Subramanya, A.[Akshayvarun], Pirsiavash, H.[Hamed],
Constrained Mean Shift Using Distant yet Related Neighbors for Representation Learning,
ECCV22(XXXI:23-41).
Springer DOI 2211
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 .


Last update:Oct 22, 2023 at 16:34:17