16.6.2.4.2 Target Tracking Techniques, Kernel Tracking

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 Tracking and Belief Propagation,
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

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. -.
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

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

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, Multiple Trackers, Multiple Models, Fusion .