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.[Dimitrios],
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.[Fumin],
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.[Botao],
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
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 .