Martinez, B.[Brais],
Binefa, X.[Xavier],
Piecewise affine kernel tracking for non-planar targets,
PR(41), No. 12, December 2008, pp. 3682-3691.
Elsevier DOI
0810
Kernel-based tracking; Multiple kernel; SSD error; Visual tracking;
Parametric motion
BibRef
Martinez, B.[Brais],
Vivet, M.[Marc],
Binefa, X.[Xavier],
Compatible Particles for Part-Based Tracking,
AMDO10(1-10).
Springer DOI
1007
BibRef
Vivet, M.[Marc],
Martínez, B.[Brais],
Binefa, X.[Xavier],
Real-Time Motion Detection for a Mobile Observer Using Multiple Kernel
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IbPRIA09(144-151).
Springer DOI
0906
BibRef
Orriols, X.,
Binefa, X.[Xavier],
Classifying periodic motions in video sequences,
ICIP03(I: 945-948).
IEEE DOI
0312
BibRef
Martínez, B.,
Pérez, A.,
Ferraz, L.,
Binefa, X.[Xavier],
Structure Restriction for Tracking Through Multiple Views and
Occlusions,
IbPRIA07(I: 121-128).
Springer DOI
0706
BibRef
Martinez, B.,
Ferraz, L.,
Binefa, X.,
Diaz-Caro, J.,
Multiple Kernel Two-Step Tracking,
ICIP06(2785-2788).
IEEE DOI
0610
BibRef
Yang, M.[Ming],
Fan, Z.M.[Zhi-Min],
Fan, J.,
Wu, Y.[Ying],
Tracking Nonstationary Visual Appearances by Data-Driven Adaptation,
IP(18), No. 7, July 2009, pp. 1633-1644.
IEEE DOI
0906
BibRef
Yang, M.[Ming],
Wu, Y.[Ying],
Tracking Non-Stationary Appearances and Dynamic Feature Selection,
CVPR05(II: 1059-1066).
IEEE DOI
0507
BibRef
Fan, Z.M.[Zhi-Min],
Yang, M.[Ming],
Wu, Y.[Ying],
Hua, G.[Gang],
Yu, T.[Ting],
Efficient Optimal Kernel Placement for Reliable Visual Tracking,
CVPR06(I: 658-665).
IEEE DOI
0606
BibRef
Fan, Z.M.[Zhi-Min],
Yang, M.[Ming],
Wu, Y.[Ying],
Multiple Collaborative Kernel Tracking,
PAMI(29), No. 7, July 2007, pp. 1268-1273.
IEEE DOI
0706
BibRef
Earlier:
CVPR05(II: 502-509).
IEEE DOI
0507
For motion fields that may not be recoverable from image measurements.
Use local motion info.
Scale and rotation changes.
BibRef
Yang, M.[Ming],
Yu, T.[Ting],
Wu, Y.[Ying],
Game-Theoretic Multiple Target Tracking,
ICCV07(1-8).
IEEE DOI
0710
BibRef
Yang, M.[Ming],
Wu, Y.[Ying],
Lao, S.H.[Shi-Hong],
Mining Auxiliary Objects for Tracking by Multibody Grouping,
ICIP07(III: 361-364).
IEEE DOI
0709
BibRef
Earlier:
Intelligent Collaborative Tracking by Mining Auxiliary Objects,
CVPR06(I: 697-704).
IEEE DOI
0606
BibRef
Yang, M.[Ming],
Wu, Y.[Ying],
Hua, G.[Gang],
Context-Aware Visual Tracking,
PAMI(31), No. 7, July 2009, pp. 1195-1209.
IEEE DOI
0905
Consider context in tracking. Integrate into tracking objects discovered
by data mining. These are persistant co-occurance and motion with the target,
easy to track.
See also Mining Compositional Features From GPS and Visual Cues for Event Recognition in Photo Collections.
BibRef
Yuan, J.S.[Jun-Song],
Wu, Y.[Ying],
Mining Visual Collocation Patterns via Self-Supervised Subspace
Learning,
SMC-B(42), No. 2, April 2012, pp. 334-346.
IEEE DOI
1204
BibRef
Yuan, J.S.[Jun-Song],
Wu, Y.[Ying],
Yang, M.[Ming],
Discovery of Collocation Patterns: from Visual Words to Visual Phrases,
CVPR07(1-8).
IEEE DOI
0706
bag-of-words.
BibRef
Yuan, J.S.[Jun-Song],
Wu, Y.[Ying],
Spatial Random Partition for Common Visual Pattern Discovery,
ICCV07(1-8).
IEEE DOI
0710
BibRef
Yuan, J.S.[Jun-Song],
Li, Z.[Zhu],
Fu, Y.[Yun],
Wu, Y.[Ying],
Huang, T.S.[Thomas S.],
Common Spatial Pattern Discovery by Efficient Candidate Pruning,
ICIP07(I: 165-168).
IEEE DOI
0709
BibRef
Zivkovic, Z.[Zoran],
Cemgil, A.T.[Ali Taylan],
Krose, B.J.A.[Ben J.A.],
Approximate Bayesian methods for kernel-based object tracking,
CVIU(113), No. 6, June 2009, pp. 743-749.
Elsevier DOI
0904
BibRef
Earlier: A1, A3, Only:
An EM-like algorithm for color-histogram-based object tracking,
CVPR04(I: 798-803).
IEEE DOI
0408
Object tracking; Approximate Bayesian filtering
BibRef
Zivkovic, Z.[Zoran],
van der Heijden, F.[Ferdinand],
Better features to track by estimating the tracking convergence region,
ICPR02(II: 635-638).
IEEE DOI
0211
BibRef
Miao, Q.[Quan],
Wang, G.J.[Gui-Jin],
Shi, C.B.[Chen-Bo],
Lin, X.G.[Xing-Gang],
Ruan, Z.W.[Zhi-Wei],
A new framework for on-line object tracking based on SURF,
PRL(32), No. 13, 1 October 2011, pp. 1564-1571.
Elsevier DOI
1109
Object tracking; Keypoint matching; On-line boosting; Adaptive
classifiers; SURF
BibRef
Miao, Q.[Quan],
Wang, G.J.[Gui-Jin],
Lin, X.G.[Xing-Gang],
Implementation of Scale and Rotation Invariant On-Line Object Tracking
Based on CUDA,
IEICE(E94-D), No. 12, December 2011, pp. 2549-2552.
WWW Link.
1112
BibRef
Miao, Q.[Quan],
Wang, G.J.[Gui-Jin],
Lin, X.G.[Xing-Gang],
Kernel-Based On-Line Object Tracking Combining both Local Description
and Global Representation,
IEICE(E96-D), No. 1, January 2013, pp. 159-162.
WWW Link.
1301
BibRef
Miao, Q.[Quan],
Wang, G.J.[Gui-Jin],
Lin, X.G.[Xing-Gang],
Wang, Y.M.[Yong-Ming],
Shi, C.B.[Chen-Bo],
Liao, C.[Chao],
Scale and rotation invariant feature-based object tracking via modified
on-line boosting,
ICIP10(3929-3932).
IEEE DOI
1009
BibRef
Li, G.R.[Guo-Rong],
Qu, W.[Wei],
Huang, Q.M.[Qing-Ming],
A Multiple Targets Appearance Tracker Based on Object Interaction
Models,
CirSysVideo(22), No. 3, March 2012, pp. 450-464.
IEEE DOI
1203
BibRef
Earlier:
Real-time interactive multi-target tracking using kernel-based trackers,
ICIP10(689-692).
IEEE DOI
1009
BibRef
Wang, Z.J.[Zhi-Jie],
Ben Salah, M.[Mohamed],
Zhang, H.[Hong],
Ray, N.[Nilanjan],
Shape based appearance model for kernel tracking,
IVC(30), No. 4-5, May 2012, pp. 332-344.
Elsevier DOI
1206
Object tracking; Appearance model; Shape cue
BibRef
Wang, Z.J.[Zhi-Jie],
Zhang, H.[Hong],
Ray, N.[Nilanjan],
Tracking of multiple interacting objects using a novel prediction model,
ICIP09(869-872).
IEEE DOI
0911
BibRef
Papoutsakis, K.E.[Konstantinos E.],
Argyros, A.A.[Antonis A.],
Integrating tracking with fine object segmentation,
IVC(31), No. 10, 2013, pp. 771-785.
Elsevier DOI
1310
BibRef
Earlier:
Object Tracking and Segmentation in a Closed Loop,
ISVC10(I: 405-416).
Springer DOI
1011
Kernel-based object tracking
BibRef
Kosmopoulos, D.I.[Dimitrios I.],
Papoutsakis, K.E.[Konstantinos E.],
Argyros, A.A.[Antonis A.],
A Framework for Online Segmentation and Classification of Modeled
Actions Performed in the Context of Unmodeled Ones,
CirSysVideo(27), No. 12, December 2017, pp. 2578-2590.
IEEE DOI
1712
BibRef
Earlier:
Segmentation and classification of modeled actions in the context of
unmodeled ones,
BMVC14(xx-yy).
HTML Version.
1410
Computational modeling, Dynamic programming,
Hidden Markov models, Support vector machines,
action spotting
BibRef
Zeng, F.X.[Fan-Xiang],
Liu, X.[Xuan],
Huang, Z.T.[Zhi-Tong],
Ji, Y.F.[Yue-Feng],
Kernel Based Multiple Cue Adaptive Appearance Model For Robust
Real-time Visual Tracking,
SPLetters(20), No. 11, 2013, pp. 1094-1097.
IEEE DOI
1310
Bayes methods
BibRef
Zoidi, O.,
Tefas, A.[Anastasios],
Pitas, I.[Ioannis],
Visual Object Tracking Based on Local Steering Kernels and Color
Histograms,
CirSysVideo(23), No. 5, May 2013, pp. 870-882.
IEEE DOI
1305
BibRef
Liu, F.H.[Fang-Hui],
Zhou, T.[Tao],
Fu, K.[Keren],
Yang, J.[Jie],
Kernelized temporal locality learning for real-time visual tracking,
PRL(90), No. 1, 2017, pp. 72-79.
Elsevier DOI
1704
Visual tracking
BibRef
Li, Y.[Yang],
Zhang, Y.F.[Ya-Fei],
Xu, Y.L.[Yu-Long],
Wang, J.B.[Jia-Bao],
Miao, Z.[Zhuang],
Robust Scale Adaptive Kernel Correlation Filter Tracker With
Hierarchical Convolutional Features,
SPLetters(23), No. 8, August 2016, pp. 1136-1140.
IEEE DOI
1608
filtering theory
BibRef
Liu, Z.G.[Zhong-Geng],
Lian, Z.C.[Zhi-Chao],
Li, Y.[Yang],
A novel adaptive kernel correlation filter tracker with multiple
feature integration,
ICIP17(2572-2576)
IEEE DOI
1803
Correlation, Estimation, Feature extraction, Image color analysis,
Robustness, Target tracking, Visualization,
Visual Tracking
BibRef
Li, Y.[Yang],
Zhu, J.K.[Jian-Ke],
A Scale Adaptive Kernel Correlation Filter Tracker with Feature
Integration,
VOT14(254-265).
Springer DOI
1504
BibRef
Zhang, B.C.[Bao-Chang],
Li, Z.G.[Zhi-Gang],
Cao, X.,
Ye, Q.,
Chen, C.,
Shen, L.,
Perina, A.[Alessandro],
Jill, R.,
Output Constraint Transfer for Kernelized Correlation Filter in
Tracking,
SMCS(47), No. 4, April 2017, pp. 693-703.
IEEE DOI
1704
Benchmark testing
BibRef
Gao, L.[Long],
Li, Y.S.[Yun-Song],
Ning, J.F.[Ji-Feng],
Improved kernelized correlation filter tracking by using spatial
regularization,
JVCIR(50), No. 1, 2018, pp. 74-82.
Elsevier DOI
1712
Visual tracking
BibRef
Chen, K.[Kai],
Tao, W.B.[Wen-Bing],
Convolutional Regression for Visual Tracking,
IP(27), No. 7, July 2018, pp. 3611-3620.
IEEE DOI
1805
Discriminatively Learned Correlation Filters (DCF).
Convolution, Correlation, Feature extraction, Kernel,
Predictive models, Training, Visualization, Visual tracking,
linear regression
BibRef
Zheng, W.W.[Wei-Wei],
Yu, H.M.[Hui-Min],
Huang, W.[Wei],
Visual tracking via Graph Regularized Kernel Correlation Filer and
Multi-Memory Voting,
JVCIR(55), 2018, pp. 688-697.
Elsevier DOI
1809
Visual object tracking,
Graph Regularized Kernel Correlation Filer, Drift handling
BibRef
Wang, J.[Jun],
Liu, W.B.[Wei-Bin],
Xing, W.W.[Wei-Wei],
Zhang, S.[Shunli],
Visual object tracking with multi-scale superpixels and color-feature
guided kernelized correlation filters,
SP:IC(63), 2018, pp. 44-62.
Elsevier DOI
1804
Visual tracking, Superpixel, Kernelized correlation filter,
Bayesian filter, Color feature guided confidence map, Multi-scale superpixels
BibRef
Yao, R.[Rui],
Xia, S.X.[Shi-Xiong],
Shen, F.M.[Fu-Min],
Zhou, Y.[Yong],
Niu, Q.[Qiang],
Exploiting Spatial Structure from Parts for Adaptive Kernelized
Correlation Filter Tracker,
SPLetters(23), No. 5, May 2016, pp. 658-662.
IEEE DOI
1604
Computational modeling
BibRef
Zhang, H.L.[Huan-Long],
Zhang, X.J.[Xiu-Jiao],
Wang, Y.[Yong],
Qian, X.L.[Xiao-Liang],
Wang, Y.F.[Yan-Feng],
Extended cuckoo search-based kernel correlation filter for abrupt
motion tracking,
IET-CV(12), No. 6, September 2018, pp. 763-769.
DOI Link
1808
BibRef
Li, C.[Ce],
Liu, X.C.[Xing-Chao],
Su, X.B.[Xiang-Bo],
Zhang, B.C.[Bao-Chang],
Robust kernelized correlation filter with scale adaption for real-time
single object tracking,
RealTimeIP(14), No. 3, October 2018, pp. 583-596.
WWW Link.
1811
BibRef
Uzkent, B.,
Rangnekar, A.,
Hoffman, M.J.,
Tracking in Aerial Hyperspectral Videos Using Deep Kernelized
Correlation Filters,
GeoRS(57), No. 1, January 2019, pp. 449-461.
IEEE DOI
1901
Hyperspectral imaging, Tracking, Computer architecture,
Correlation, Videos, Training, Deep features, hyperspectral sensing,
vehicle tracking
BibRef
Ruan, W.J.[Wei-Jian],
Chen, J.[Jun],
Wu, Y.[Yi],
Wang, J.Q.[Jin-Qiao],
Liang, C.[Chao],
Hu, R.M.[Rui-Min],
Jiang, J.J.[Jun-Jun],
Multi-Correlation Filters With Triangle-Structure Constraints for
Object Tracking,
MultMed(21), No. 5, May 2019, pp. 1122-1134.
IEEE DOI
1905
correlation methods, filtering theory, object detection,
object tracking, target tracking, multiple CFs, global object,
high integrity
BibRef
Tang, M.[Ming],
Yu, B.[Bin],
Zhang, F.[Fan],
Wang, J.Q.[Jin-Qiao],
High-Speed Tracking with Multi-kernel Correlation Filters,
CVPR18(4874-4883)
IEEE DOI
1812
Kernel, Correlation, Linear programming, Target tracking,
Upper bound, Training
BibRef
Tang, M.[Ming],
Feng, J.Y.[Jia-Yi],
Multi-kernel Correlation Filter for Visual Tracking,
ICCV15(3038-3046)
IEEE DOI
1602
Correlation
BibRef
Gong, L.[Lin],
Mo, Z.C.[Zhen-Chong],
Zhao, S.N.[Shang-Nan],
Song, Y.[Yong],
An improved Kernelized Correlation Filter tracking algorithm based on
multi-channel memory model,
SP:IC(78), 2019, pp. 200-205.
Elsevier DOI
1909
Multi-channel memory, Kernelized Correlation Filter, Target tracking
BibRef
Shao, J.,
Du, B.,
Wu, C.,
Zhang, L.,
Can We Track Targets From Space? A Hybrid Kernel Correlation Filter
Tracker for Satellite Video,
GeoRS(57), No. 11, November 2019, pp. 8719-8731.
IEEE DOI
1911
Target tracking, Satellites, Correlation, Feature extraction,
Streaming media, Kernel, Histogram of oriented gradient (HOG),
satellite video tracking
BibRef
Mbelwa, J.T.[Jimmy T.],
Zhao, Q.J.[Qing-Jie],
Wang, F.S.[Fa-Sheng],
Visual tracking tracker via object proposals and co-trained kernelized
correlation filters,
VC(36), No. 6, June 2020, pp. 1173-1187.
WWW Link.
2005
BibRef
Fan, B.,
Cong, Y.,
Tian, J.,
Tang, Y.,
Reliable Multi-Kernel Subtask Graph Correlation Tracker,
IP(29), 2020, pp. 8120-8133.
IEEE DOI
2008
Target tracking, Correlation, Kernel, Feature extraction, Robustness,
Laplace equations, Layered multi-subtask learning,
object tracking
BibRef
Wang, J.,
Zheng, L.,
Tang, M.,
Feng, J.,
A Comparison of Correlation Filter-Based Trackers and Struck Trackers,
CirSysVideo(30), No. 9, September 2020, pp. 3106-3118.
IEEE DOI
2009
Correlation, Target tracking, Kernel, Support vector machines,
Training, Optimization, Discrete Fourier transforms,
ranking SVM tracker
BibRef
Nousi, P.[Paraskevi],
Tefas, A.[Anastasios],
Pitas, I.[Ioannis],
Dense convolutional feature histograms for robust visual object
tracking,
IVC(99), 2020, pp. 103933.
Elsevier DOI
2006
Object Tracking, Deep Learning, Bag-of-Features,
Convolutional Feature Histograms
BibRef
Nousi, P.[Paraskevi],
Triantafyllidou, D.[Danai],
Tefas, A.[Anastasios],
Pitas, I.[Ioannis],
Re-identification framework for long term visual object tracking
based on object detection and classification,
SP:IC(88), 2020, pp. 115969.
Elsevier DOI
2009
Visual object tracking, Long-term tracking, Re-detection, Deep learning
BibRef
Wang, B.T.[Bo-Tao],
Xiong, H.K.[Hong-Kai],
Jiang, X.Q.[Xiao-Qian],
Zheng, Y.F.,
Data-Driven Hierarchical Structure Kernel for Multiscale Part-Based
Object Recognition,
IP(23), No. 4, April 2014, pp. 1765-1778.
IEEE DOI
1404
computer vision
BibRef
Li, X.[Xi],
Dick, A.[Anthony],
Shen, C.H.[Chun-Hua],
van den Hengel, A.J.[Anton J.],
Wang, H.Z.[Han-Zi],
Incremental Learning of 3D-DCT Compact Representations for Robust
Visual Tracking,
PAMI(35), No. 4, April 2013, pp. 863-881.
IEEE DOI
1303
BibRef
Earlier: A1, A2, A5, A3, A4:
Graph mode-based contextual kernels for robust SVM tracking,
ICCV11(1156-1163).
IEEE DOI
1201
Tracking with more than binary constraints.
BibRef
Li, X.[Xi],
Dick, A.,
Shen, C.H.[Chun-Hua],
Zhang, Z.F.[Zhong-Fei],
van den Hengel, A.J.,
Wang, H.Z.[Han-Zi],
Visual Tracking With Spatio-Temporal Dempster-Shafer Information Fusion,
IP(22), No. 8, 2013, pp. 3028-3040.
IEEE DOI
1307
Bayes methods; SVM classifier; visual tracking
BibRef
Wu, Q.Q.[Qiang-Qiang],
Yan, Y.[Yan],
Liang, Y.J.[Yan-Jie],
Liu, Y.[Yi],
Wang, H.Z.[Han-Zi],
DSNet: Deep and Shallow Feature Learning for Efficient Visual Tracking,
ACCV18(V:119-134).
Springer DOI
1906
BibRef
Liu, F.[Fayao],
Shen, C.H.[Chun-Hua],
Reid, I.D.[Ian D.],
van den Hengel, A.J.[Anton J.],
Online unsupervised feature learning for visual tracking,
IVC(51), No. 1, 2016, pp. 84-94.
Elsevier DOI
1606
Object tracking
BibRef
Li, X.[Xi],
Shen, C.H.[Chun-Hua],
Dick, A.[Anthony],
van den Hengel, A.J.[Anton J.],
Learning Compact Binary Codes for Visual Tracking,
CVPR13(2419-2426)
IEEE DOI
1309
SVM; Visual Tracking; appearance model; hashing; hypergraph
BibRef
Kumar, P.[Pankaj],
Dick, A.[Anthony],
Brooks, M.J.[Michael J.],
Multiple target tracking with an efficient compact colour correlogram,
ICARCV08(699-704).
IEEE DOI
1109
BibRef
And:
Integrated Bayesian multi-cue tracker for objects observed from moving
cameras,
IVCNZ08(1-6).
IEEE DOI
0811
BibRef
Earlier: A1, A3, A2:
Adaptive Multiple Object Tracking Using Colour and Segmentation Cues,
ACCV07(I: 853-863).
Springer DOI
0711
BibRef
Kumar, P.[Pankaj],
Dick, A.[Anthony],
Adaptive earth movers distance-based Bayesian multi-target tracking,
IET-CV(7), No. 4, 2013, pp. 246-257.
DOI Link
1307
BibRef
Li, X.[Xi],
Shen, C.H.[Chun-Hua],
Dick, A.[Anthony],
Zhang, Z.F.M.[Zhong-Fei Mark],
Zhuang, Y.T.[Yue-Ting],
Online Metric-Weighted Linear Representations for Robust Visual
Tracking,
PAMI(38), No. 5, May 2016, pp. 931-950.
IEEE DOI
1604
feature extraction
BibRef
Li, X.[Xi],
Shen, C.H.[Chun-Hua],
Shi, Q.F.[Qin-Feng],
Dick, A.[Anthony],
van den Hengel, A.J.[Anton J.],
Non-sparse linear representations for visual tracking with online
reservoir metric learning,
CVPR12(1760-1767).
IEEE DOI
1208
BibRef
Yao, R.[Rui],
Robust Model-Free Multi-Object Tracking with Online Kernelized
Structural Learning,
SPLetters(22), No. 12, December 2015, pp. 2401-2405.
IEEE DOI
1512
learning (artificial intelligence)
BibRef
Yao, R.[Rui],
Shi, Q.F.[Qin-Feng],
Shen, C.H.[Chun-Hua],
Zhang, Y.N.[Yan-Ning],
van den Hengel, A.J.[Anton J.],
Part-Based Robust Tracking Using Online Latent Structured Learning,
CirSysVideo(27), No. 6, June 2017, pp. 1235-1248.
IEEE DOI
1706
BibRef
Earlier:
Part-Based Visual Tracking with Online Latent Structural Learning,
CVPR13(2363-2370)
IEEE DOI
1309
BibRef
Earlier:
Robust Tracking with Weighted Online Structured Learning,
ECCV12(III: 158-172).
Springer DOI
1210
Computational modeling, Deformable models, Object tracking,
Robustness, Support vector machines, Target tracking,
Visualization, Online latent structured learning,
part-based model, visual tracking.
online structural learning;
BibRef
Kumar, P.[Pankaj],
Brooks, M.J.[Michael J.],
van den Hengel, A.J.[Anton J.],
An Adaptive Bayesian Technique for Tracking Multiple Objects,
PReMI07(657-665).
Springer DOI
0712
BibRef
Liu, C.Y.[Chong-Yu],
Yao, R.[Rui],
Rezatofighi, S.H.[S. Hamid],
Reid, I.D.[Ian D.],
Shi, Q.F.[Qin-Feng],
Model-Free Tracker for Multiple Objects Using Joint Appearance and
Motion Inference,
IP(29), No. 1, 2020, pp. 277-288.
IEEE DOI
1910
BibRef
Earlier:
Multi-Object Model-Free Tracking with Joint Appearance and Motion
Inference,
DICTA17(1-8)
IEEE DOI
1804
inference mechanisms, learning (artificial intelligence),
motion estimation, neural nets, object recognition,
graphical models.
object detection, object tracking, optimisation, tracking,
Visualization
BibRef
Yan, Q.S.[Qing-Sen],
Li, L.S.[Lin-Sheng],
Kernel sparse tracking with compressive sensing,
IET-CV(8), No. 4, August 2014, pp. 305-315.
DOI Link
1407
Appearance changes. Use 2 stage sparse representation.
BibRef
Bai, Y.C.[Yan-Cheng],
Tang, M.[Ming],
Object Tracking via Robust Multitask Sparse Representation,
SPLetters(21), No. 8, August 2014, pp. 909-913.
IEEE DOI
1406
BibRef
Earlier:
Robust tracking via weakly supervised ranking SVM,
CVPR12(1854-1861).
IEEE DOI
1208
BibRef
Earlier:
Robust visual tracking via ranking SVM,
ICIP11(517-520).
IEEE DOI
1201
Joints
BibRef
Bai, Y.C.[Yan-Cheng],
Tang, M.[Ming],
Robust visual tracking via augmented kernel SVM,
IVC(32), No. 8, 2014, pp. 465-475.
Elsevier DOI
1407
Feature representation
BibRef
Choi, H.S.[Hong Seok],
Kim, I.S.[In Su],
Choi, J.Y.[Jin Young],
Combining histogram-wise and pixel-wise matchings for kernel tracking
through constrained optimization,
CVIU(118), No. 1, 2014, pp. 61-70.
Elsevier DOI
1312
Object tracking
BibRef
Ma, C.[Chao],
Liu, C.C.[Chuan-Cai],
Two dimensional hashing for visual tracking,
CVIU(135), No. 1, 2015, pp. 83-94.
Elsevier DOI
1504
Hashing
BibRef
Qian, C.,
Xu, Z.,
Robust Visual Tracking via Sparse Representation Under Subclass
Discriminant Constraint,
CirSysVideo(26), No. 7, July 2016, pp. 1293-1307.
IEEE DOI
1608
image coding
BibRef
Zhang, L.[Le],
Suganthan, P.N.[Ponnuthurai Nagaratnam],
Robust visual tracking via co-trained Kernelized correlation filters,
PR(69), No. 1, 2017, pp. 82-93.
Elsevier DOI
1706
Visual tracking
BibRef
Zhang, L.[Le],
Suganthan, P.N.[Ponnuthurai Nagaratnam],
Visual Tracking With Convolutional Random Vector Functional Link
Network,
Cyber(47), No. 10, October 2017, pp. 3243-3253.
IEEE DOI
1709
Biological neural networks, Data models, Target tracking, Training,
convolutional random vector functional link (CRVFL),
deep learning, random vector functional link (RVFL), visual, tracking
BibRef
Hu, M.H.[Ming-Hui],
Suganthan, P.N.,
Representation learning using deep random vector functional link
networks for clustering,
PR(129), 2022, pp. 108744.
Elsevier DOI
2206
Random vector functional link, Unsupervised learning,
Consensus clustering, Manifold regularization
BibRef
Shi, Q.[Qiushi],
Katuwal, R.[Rakesh],
Suganthan, P.N.,
Tanveer, M.,
Random vector functional link neural network based ensemble deep
learning,
PR(117), 2021, pp. 107978.
Elsevier DOI
2106
Random Vector Functional Link (RVFL), Deep RVFL,
Multi-layer RVFL, Ensemble deep learning, Extreme learning machine (ELM)
BibRef
Farahi, F.[Fahime],
Yazdi, H.S.[Hadi Sadoghi],
Probabilistic Kalman filter for moving object tracking,
SP:IC(82), 2020, pp. 115751.
Elsevier DOI
2001
Kalman filter, Learned tracker, Smoothing process, Graph
BibRef
Huang, B.[Bo],
Xu, T.F.[Ting-Fa],
Jiang, S.W.[Shen-Wang],
Chen, Y.W.[Yi-Wen],
Bai, Y.[Yu],
Robust Visual Tracking via Constrained Multi-Kernel Correlation
Filters,
MultMed(22), No. 11, November 2020, pp. 2820-2832.
IEEE DOI
2010
Kernel, Correlation, Target tracking, Adaptation models, Training,
Frequency-domain analysis, Feature extraction,
adaptive updating
BibRef
Kutschbach, T.,
Bochinski, E.,
Eiselein, V.,
Sikora, T.,
Sequential sensor fusion combining probability hypothesis density and
kernelized correlation filters for multi-object tracking in video
data,
AVSS17(1-5)
IEEE DOI
1806
Gaussian processes, filtering theory, object tracking,
video signal processing, GMPHD tracking-by-detection scheme,
Visualization
BibRef
Bibi, A.[Adel],
Mueller, M.[Matthias],
Ghanem, B.[Bernard],
Target Response Adaptation for Correlation Filter Tracking,
ECCV16(VI: 419-433).
Springer DOI
1611
BibRef
Earlier: A1, A3, Only:
Multi-template Scale-Adaptive Kernelized Correlation Filters,
VOT15(613-620)
IEEE DOI
1602
Correlation
Drawbacks of Kernelized Correlation Filter (KCF) tracker. Some alternatives.
BibRef
Montero, A.S.,
Lang, J.,
Laganiere, R.,
Scalable Kernel Correlation Filter with Sparse Feature Integration,
VOT15(587-594)
IEEE DOI
1602
Computational modeling
BibRef
Ge, T.[Ting],
Lu, Y.[Yao],
Multiple kernel boosting based tracking using pooling features,
ICIP15(3210-3214)
IEEE DOI
1512
multiple kernel boosting; object tracking; pooling
BibRef
Li, P.[Peng],
Cai, Z.P.[Zhi-Peng],
Wang, C.[Cheng],
Sun, Z.[Zhuo],
Wang, H.Y.[Han-Yun],
Li, J.[Jonathan],
Cascade framework for object extraction in image sequences,
CVRS12(58-62).
IEEE DOI
1302
BibRef
Li, P.[Peng],
Cai, Z.P.[Zhi-Peng],
Wang, H.Y.[Han-Yun],
Sun, Z.[Zhuo],
Yi, Y.[Yunhui],
Wang, C.[Cheng],
Li, J.[Jonathan],
Scale invariant kernel-based object tracking,
CVRS12(252-255).
IEEE DOI
1302
BibRef
Zulkifley, M.A.[Mohd Asyraf],
Moran, B.[Bill],
Statistical Patch-Based Observation for Single Object Tracking,
CIAP11(II: 119-129).
Springer DOI
1109
BibRef
And:
Getting Robust Observation for Single Object Tracking:
A Statistical Kernel-Based Approach,
CAIP11(I: 351-359).
Springer DOI
1109
BibRef
Nguyen, Q.A.[Quang Anh],
Robles-Kelly, A.[Antonio],
Zhou, J.[Jun],
A Graph-Based Feature Combination Approach to Object Tracking,
ACCV09(II: 224-235).
Springer DOI
0909
BibRef
Majeed, I.,
Arif, O.,
Kernel Subspace Integral Image Based Probabilistic Visual Object
Tracking,
DICTA15(1-7)
IEEE DOI
1603
estimation theory
BibRef
Arif, O.[Omar],
Vela, P.A.[Patricio Antonio],
Non-rigid Object Localization and Segmentation Using Eigenspace
Representation,
ICCV09(803-808).
IEEE DOI
0909
BibRef
Arif, O.[Omar],
Vela, P.A.[Patricio Antonio],
Kernel map compression using generalized radial basis functions,
ICCV09(1119-1124).
IEEE DOI
0909
BibRef
And:
Kernel covariance image region description for object tracking,
ICIP09(865-868).
IEEE DOI
0911
BibRef
And:
Robust Density Comparison for Visual Tracking,
BMVC09(xx-yy).
PDF File.
0909
BibRef
Ma, L.[Lili],
Cheng, J.[Jian],
Lu, H.Q.[Han-Qing],
Multi-cue collaborative kernel tracking with cross ratio invariant
constraint,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Megret, R.[Rémi],
Mikram, M.[Mounia],
Berthoumieu, Y.[Yannick],
Inverse Composition for Multi-kernel Tracking,
ICCVGIP06(480-491).
Springer DOI
0612
BibRef
Tyagi, A.[Ambrish],
Davis, J.W.[James W.],
A Context-Based Tracker Switching Framework,
Motion08(1-8).
IEEE DOI
0801
BibRef
Tyagi, A.[Ambrish],
Davis, J.W.[James W.],
Potamianos, G.[Gerasimos],
Steepest Descent For Efficient Covariance Tracking,
Motion08(1-6).
IEEE DOI
0801
BibRef
Tyagi, A.[Ambrish],
Keck, Jr., M.A.[Mark A.],
Davis, J.W.[James W.],
Potamianos, G.[Gerasimos],
Kernel-Based 3D Tracking,
VS07(1-8).
IEEE DOI
0706
BibRef
Tyagi, A.[Ambrish],
Potamianos, G.[Gerasimos],
Davis, J.W.[James W.],
Chu, S.M.[Stephen M.],
Fusion of Multiple Camera Views for Kernel-Based 3D Tracking,
Motion07(1-1).
IEEE DOI
0702
BibRef
Dewan, M.[Maneesh],
Toward Optimal Kernel-based Tracking,
CVPR06(I: 618-625).
IEEE DOI
0606
BibRef
Hager, G.D.,
Dewan, M.,
Stewart, C.V.,
Multiple kernel tracking with SSD,
CVPR04(I: 790-797).
IEEE DOI
0408
More efficient matching.
See also Kernel Smoothing.
BibRef
Peng, N.S.[Ning-Song],
Yang, J.[Jie],
Chen, J.X.[Jia-Xin],
Kernel-Bandwidth Adaptation for Tracking Object Changing in Size,
ICIAR04(II: 581-588).
Springer DOI
0409
BibRef
Liu, Z.[Zhi],
Shen, L.Q.[Li-Quan],
Han, Z.M.[Zhong-Min],
Zhang, Z.Y.[Zhao-Yang],
A Novel Video Object Tracking Approach Based on Kernel Density
Estimation and Markov Random Field,
ICIP07(III: 373-376).
IEEE DOI
0709
BibRef
Nguyen, Q.A.[Quang Anh],
Robles-Kelly, A.[Antonio],
Shen, C.H.[Chun-Hua],
Kernel-based Tracking from a Probabilistic Viewpoint,
CVPR07(1-8).
IEEE DOI
0706
BibRef
Earlier:
Enhanced Kernel-Based Tracking for Monochromatic and Thermographic
Video,
AVSBS06(28-28).
IEEE DOI
0611
BibRef
Parameswaran, V.[Vasu],
Ramesh, V.[Visvanathan],
Zoghlami, I.[Imad],
Tunable Kernels for Tracking,
CVPR06(II: 2179-2186).
IEEE DOI
0606
BibRef
Namboodiri, V.P.[Vinay P.],
Ghorawat, A.[Amit],
Chaudhuri, S.[Subhasis],
Improved Kernel-Based Object Tracking Under Occluded Scenarios,
ICCVGIP06(504-515).
Springer DOI
0612
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Target Tracking Techniques, Kalman Filters .