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MVA(8), No. 5, 1995, pp. 275-288.
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9500
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Novel design for real time path tracking with computer vision using
neural networks,
IJCVR(1), No. 4, 2010, pp. 380-391.
DOI Link
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Mei, X.[Xue],
Ling, H.B.[Hai-Bin],
Robust Visual Tracking and Vehicle Classification via Sparse
Representation,
PAMI(33), No. 11, November 2011, pp. 2259-2272.
IEEE DOI
1110
BibRef
Earlier:
Robust Visual Tracking Using L1 Minimization,
ICCV09(1436-1443).
IEEE DOI
PDF File.
0909
See also Illumination Recovery From Image With Cast Shadows Via Sparse Representation.
BibRef
Fan, H.[Heng],
Ling, H.B.[Hai-Bin],
Parallel Tracking and Verifying: A Framework for Real-Time and High
Accuracy Visual Tracking,
ICCV17(5487-5495)
IEEE DOI
1802
BibRef
And:
SANet: Structure-Aware Network for Visual Tracking,
DeepLearn-T17(2217-2224)
IEEE DOI
1709
SLAM (robots), learning (artificial intelligence),
multi-threading, object tracking, parallel processing,
Visualization.
Computational modeling, Feature extraction,
Recurrent neural networks, Robustness, Target tracking.
BibRef
Li, H.X.[Han-Xi],
Li, Y.[Yi],
Porikli, F.M.[Fatih M.],
DeepTrack: Learning Discriminative Feature Representations Online for
Robust Visual Tracking,
IP(25), No. 4, April 2016, pp. 1834-1848.
IEEE DOI
1604
BibRef
Earlier:
DeepTrack: Learning Discriminative Feature Representations by
Convolutional Neural Networks for Visual Tracking,
BMVC14(xx-yy).
HTML Version.
1410
BibRef
Li, H.X.[Han-Xi],
Li, Y.[Yi],
Porikli, F.M.[Fatih M.],
Convolutional neural net bagging for online visual tracking,
CVIU(153), No. 1, 2016, pp. 120-129.
Elsevier DOI
1612
Visual tracking
BibRef
Earlier:
Robust Online Visual Tracking with a Single Convolutional Neural
Network,
ACCV14(V: 194-209).
Springer DOI
1504
Feature extraction
BibRef
Hu, H.,
Ma, B.,
Shen, J.,
Sun, H.,
Shao, L.,
Porikli, F.M.[Fatih M.],
Robust Object Tracking Using Manifold Regularized Convolutional
Neural Networks,
MultMed(21), No. 2, February 2019, pp. 510-521.
IEEE DOI
1902
Visualization, Manifolds, Target tracking, Laplace equations,
Training, Feature extraction, Convolutional neural networks,
online tracking
BibRef
Zhu, H.[Hao],
Porikli, F.M.[Fatih M.],
Automatic Refinement Strategies for Manual Initialization of Object
Trackers,
IP(26), No. 2, February 2017, pp. 821-835.
IEEE DOI
1702
computer vision
BibRef
Zhu, G.[Gao],
Porikli, F.M.[Fatih M.],
Li, H.D.[Hong-Dong],
Not All Negatives Are Equal:
Learning to Track With Multiple Background Clusters,
CirSysVideo(28), No. 2, February 2018, pp. 314-326.
IEEE DOI
1802
BibRef
Earlier:
Model-Free Multiple Object Tracking with Shared Proposals,
ACCV16(II: 288-304).
Springer DOI
1704
BibRef
And:
Beyond Local Search:
Tracking Objects Everywhere with Instance-Specific Proposals,
CVPR16(943-951)
IEEE DOI
1612
BibRef
And:
Robust Visual Tracking with Deep Convolutional Neural Network Based
Object Proposals on PETS,
PETS16(1265-1272)
IEEE DOI
1612
Context, Object tracking, Support vector machines, Training,
Visualization, Contextual clustering, fine-grained model,
tracking by detection
BibRef
Hussein, M.[Mohamed],
Porikli, F.M.[Fatih M.],
Li, R.[Rui],
Arslan, S.[Suayb],
CrossTrack: Robust 3D tracking from two cross-sectional views,
CVPR11(1041-1048).
IEEE DOI
1106
BibRef
Ma, B.,
Huang, L.,
Shen, J.,
Shao, L.,
Yang, M.H.,
Porikli, F.M.,
Visual Tracking Under Motion Blur,
IP(25), No. 12, December 2016, pp. 5867-5876.
IEEE DOI
1612
image motion analysis
BibRef
Huang, L.,
Ma, B.,
Shen, J.,
He, H.,
Shao, L.,
Porikli, F.M.[Fatih M.],
Visual Tracking by Sampling in Part Space,
IP(26), No. 12, December 2017, pp. 5800-5810.
IEEE DOI
1710
image sampling, object tracking,
probability sampling,
Part space,
BibRef
Ma, B.,
Hu, H.,
Shen, J.,
Zhang, Y.,
Porikli, F.M.[Fatih M.],
Linearization to Nonlinear Learning for Visual Tracking,
ICCV15(4400-4407)
IEEE DOI
1602
Dictionaries
BibRef
Guo, J.,
Xu, T.,
Deep Ensemble Tracking,
SPLetters(24), No. 10, October 2017, pp. 1562-1566.
IEEE DOI
1710
convolution, feature extraction, feedforward neural nets,
distance metric, template matching problem.
BibRef
Cao, Y.[Yi],
Ji, H.B.[Hong-Bing],
Zhang, W.[Wenbo],
Xue, F.[Fei],
Learning spatio-temporal context via hierarchical features for visual
tracking,
SP:IC(66), 2018, pp. 50-65.
Elsevier DOI
1806
Visual tracking, Convolutional neural network,
Transfer learning, Spatio-temporal context,
Training confidence index
BibRef
Cao, Y.[Yi],
Ji, H.B.[Hong-Bing],
Zhang, W.[Wenbo],
Xue, F.[Fei],
Visual tracking via dynamic weighting with pyramid-redetection based
Siamese networks,
JVCIR(65), 2019, pp. 102635.
Elsevier DOI
1912
Visual tracking, Siamese networks, Dynamic weighting,
Residual structure, Convolutional neural networks, Pyramid-redetection
BibRef
Zhu, Z.G.[Zhi-Gang],
Ji, H.B.[Hong-Bing],
Zhang, W.[Wenbo],
Huang, G.P.[Guo-Peng],
Temporal stochastic linear encoding networks,
SP:IC(70), 2019, pp. 14-20.
Elsevier DOI
1812
Convolutional neural network, Action recognition,
Long-range temporal dynamics, Motion boundary
BibRef
Hu, X.P.[Xiao-Peng],
Li, J.T.[Jing-Ting],
Yang, Y.[Yan],
Wang, F.[Fan],
Reliability verification-based convolutional neural networks for object
tracking,
IET-IPR(13), No. 1, January 2019, pp. 175-185.
DOI Link
1812
BibRef
Wang, T.[Tao],
Ling, H.B.[Hai-Bin],
Gracker: A Graph-Based Planar Object Tracker,
PAMI(40), No. 6, June 2018, pp. 1494-1501.
IEEE DOI
1805
Algorithm design and analysis, Benchmark testing,
Object tracking, Robustness, Target tracking, Visualization,
pose estimation
BibRef
Li, Y.D.[Yun-Dong],
Zhang, X.[Xueyan],
Li, H.G.[Hong-Guang],
Zhou, Q.C.[Qi-Chen],
Cao, X.B.[Xian-Bin],
Xiao, Z.F.[Zhi-Feng],
Object detection and tracking under Complex environment using deep
learning-based LPM,
IET-CV(13), No. 2, March 2019, pp. 157-164.
DOI Link
1902
BibRef
Jiang, X.L.[Xiao-Long],
Xiao, Z.[Zehao],
Zhang, B.C.[Bao-Chang],
Cao, X.B.[Xian-Bin],
ASiam: adaptive Siamese regression tracking with adversarial template
generation and motion-based failure recovery,
IET-IPR(13), No. 14, 12 December 2019, pp. 2694-2705.
DOI Link
1912
BibRef
Tang, F.H.[Fu-Hui],
Lu, X.K.[Xian-Kai],
Zhang, X.Y.[Xiao-Yu],
Luo, L.K.[Ling-Kun],
Hu, S.Q.[Shi-Qiang],
Zhang, H.L.[Huan-Long],
Adaptive convolutional layer selection based on historical retrospect
for visual tracking,
IET-CV(13), No. 3, April 2019, pp. 345-353.
DOI Link
1904
BibRef
Li, N.[Ning],
Ji, Q.G.[Qing-Ge],
Ma, T.J.[Tian-Jun],
ACT: an ACTNet for visual tracking,
IET-IPR(13), No. 5, 18 April 2019, pp. 722-728.
DOI Link
1904
BibRef
Dong, X.P.[Xing-Ping],
Shen, J.B.[Jian-Bing],
Wu, D.M.[Dong-Ming],
Guo, K.[Kan],
Jin, X.G.[Xiao-Gang],
Porikli, F.M.[Fatih M.],
Quadruplet Network With One-Shot Learning for Fast Visual Object
Tracking,
IP(28), No. 7, July 2019, pp. 3516-3527.
IEEE DOI
1906
image representation, learning (artificial intelligence),
object tracking, one-shot learning, fast visual object tracking,
Siamese deep network
BibRef
Zhao, F.,
Wang, J.,
Wu, Y.,
Tang, M.,
Adversarial Deep Tracking,
CirSysVideo(29), No. 7, July 2019, pp. 1998-2011.
IEEE DOI
1907
Target tracking, Visualization, Task analysis, Training,
Computational modeling, Neural networks, Correlation,
attention
BibRef
Teng, Z.[Zhu],
Xing, J.L.[Jun-Liang],
Wang, Q.[Qiang],
Zhang, B.P.[Bao-Peng],
Fan, J.P.[Jian-Ping],
Deep Spatial and Temporal Network for Robust Visual Object Tracking,
IP(29), No. 1, 2020, pp. 1762-1775.
IEEE DOI
1912
Target tracking, Visualization, Biological system modeling,
Correlation, Training, Benchmark testing, Visual tracking,
spatial-temporal LSTM
BibRef
Teng, Z.[Zhu],
Xing, J.L.[Jun-Liang],
Wang, Q.[Qiang],
Lang, C.Y.[Cong-Yan],
Feng, S.H.[Song-He],
Jin, Y.[Yi],
Robust Object Tracking Based on Temporal and Spatial Deep Networks,
ICCV17(1153-1162)
IEEE DOI
1802
feature extraction, learning (artificial intelligence),
neural nets, object detection, object tracking, Feature Net,
Visualization
BibRef
Ge, S.,
Luo, Z.,
Zhang, C.,
Hua, Y.,
Tao, D.,
Distilling Channels for Efficient Deep Tracking,
IP(29), 2020, pp. 2610-2621.
IEEE DOI
2001
Image coding, Visualization, Correlation, Feature extraction,
Adaptation models, Benchmark testing, Minimization,
CNNs
BibRef
Xu, M.X.[Meng-Xi],
Lv, L.[Li],
Luan, H.[Hui],
Huang, C.R.[Chen-Rong],
Fan, T.H.[Tang-Huai],
Object tracking based on learning collaborative representation with
adaptive weight,
SIViP(14), No. 2, March 2020, pp. 267-275.
Springer DOI
2003
BibRef
Chen, R.[Rui],
Tong, Y.[Ying],
Liang, R.[Ruiyu],
Real-Time Generic Object Tracking via Recurrent Regression Network,
IEICE(E103-D), No. 3, March 2020, pp. 602-611.
WWW Link.
2003
BibRef
Huang, K.N.[Kai-Ning],
Shi, Y.[Yan],
Zhao, F.[Fuqi],
Zhang, Z.J.[Zi-Jun],
Tu, S.S.[Shan-Shan],
Multiple instance deep learning for weakly-supervised visual object
tracking,
SP:IC(84), 2020, pp. 115807.
Elsevier DOI
2004
Multiple instance learning (MIL), Weakly-supervised,
Object tracking, Multi-view feature learning, Gaussian mixture model
BibRef
Tian, S.J.[Sheng-Jing],
Shen, S.W.[Shu-Wei],
Tian, G.Q.A.[Guo-Qi-Ang],
Liu, X.P.[Xiu-Ping],
Yin, B.C.[Bao-Cai],
End-to-end deep metric network for visual tracking,
VC(36), No. 6, June 2020, pp. 1219-1232.
WWW Link.
2005
BibRef
Zhang, Y.[Yang],
Tian, X.L.[Xiao-Lin],
Jia, N.[Nan],
Wang, F.[Fengge],
Jiao, L.C.[Li-Cheng],
Deep tracking using double-correlation filters by membership weighted
decision,
PRL(136), 2020, pp. 161-167.
Elsevier DOI
2008
Visual object tracking, Double-Correlation filter, Membership decision
BibRef
Ge, Y.[Yao],
Chen, R.[Rui],
Tong, Y.[Ying],
Cao, X.H.[Xue-Hong],
Liang, R.Y.[Rui-Yu],
Combining Siamese Network and Regression Network for Visual Tracking,
IEICE(E103-D), No. 8, August 2020, pp. 1924-1927.
WWW Link.
2008
BibRef
Fu, H.C.[Heng-Cheng],
Zhou, W.N.[Wu-Neng],
Wang, X.F.[Xiao-Feng],
Zhang, H.L.[Huan-Long],
Fast and robust visual tracking with hard balanced focal loss and
guided domain adaption,
IVC(100), 2020, pp. 103929.
Elsevier DOI
2008
Visual tracking, Siamese network, Domain adaptation, Hard balanced focal loss
BibRef
Liu, C.,
Liu, P.,
Zhao, W.,
Tang, X.,
Visual Tracking by Structurally Optimizing Pre-Trained CNN,
CirSysVideo(30), No. 9, September 2020, pp. 3153-3166.
IEEE DOI
2009
Target tracking, Visualization, Feature extraction, Task analysis,
Image reconstruction, Convolutional codes, Deep learning, one-shot learning
BibRef
Li, C.Y.[Chun-Yu],
Li, G.[Gang],
Learning multiple instance deep representation for objects tracking,
JVCIR(71), 2020, pp. 102737.
Elsevier DOI
2009
Object tracking, Convolutional networks, Multiple Instance Learning
BibRef
Han, Y.M.[Ya-Min],
Zhang, P.[Peng],
Zhuo, T.[Tao],
Huang, W.[Wei],
Zha, Y.F.[Yu-Fei],
Zhang, Y.N.[Yan-Ning],
Ensemble Tracking Based on Diverse Collaborative Framework With
Multi-Cue Dynamic Fusion,
MultMed(22), No. 10, October 2020, pp. 2698-2710.
IEEE DOI
2009
Target tracking, Correlation, Robustness, Adaptation models,
Training, Tracking loops, Collaboration, Ensembling structure,
heuristic frequency
BibRef
Xu, Q.[Qi],
Wang, H.B.[Hua-Bin],
Wu, Q.[Qilin],
Tao, L.[Liang],
Robust online tracking via sparse gradient convolution networks,
SP:IC(90), 2021, pp. 116056.
Elsevier DOI
2012
Online tracking, Convolutional networks, Gradient features,
Sparse representation
BibRef
Pu, S.,
Song, Y.,
Ma, C.,
Zhang, H.,
Yang, M.H.,
Learning Recurrent Memory Activation Networks for Visual Tracking,
IP(30), 2021, pp. 725-738.
IEEE DOI
2012
Target tracking, Visualization, Coherence, Generators, Training,
Correlation, Recurrent neural networks, Visual tracking,
representation
BibRef
Tian, S.J.[Sheng-Jing],
Liu, X.P.[Xiu-Ping],
Liu, M.[Meng],
Li, S.H.[Shu-Hua],
Yin, B.C.[Bao-Cai],
Siamese Tracking Network With Informative Enhanced Loss,
MultMed(23), 2021, pp. 120-132.
IEEE DOI
2012
Logistics, Target tracking, Training, Real-time systems,
Machine learning, Benchmark testing, Correlation, Visual tracking,
deep learning
BibRef
Xiang, J.,
Xu, G.,
Ma, C.,
Hou, J.,
End-to-End Learning Deep CRF Models for Multi-Object Tracking Deep
CRF Models,
CirSysVideo(31), No. 1, January 2021, pp. 275-288.
IEEE DOI
2101
Target tracking, Machine learning, Recurrent neural networks,
Optimization, Task analysis, Standards, Inference algorithms,
data association
BibRef
Liao, B.Y.[Bing-Yan],
Wang, C.Y.[Chen-Ye],
Wang, Y.[Yayun],
Wang, Y.N.[Yao-Nong],
Yin, J.[Jun],
PG-Net: Pixel to Global Matching Network for Visual Tracking,
ECCV20(XXII:429-444).
Springer DOI
2011
BibRef
Zhang, R.,
Fan, C.,
Ming, Y.,
Fu, H.,
Meng, X.,
An Effective Hierarchical Resolution Learning Method for
Low-Resolution Targets Tracking,
ICIP20(2076-2080)
IEEE DOI
2011
Target tracking, Spatial resolution, Shape, Visualization,
Image reconstruction, Image edge detection, Visual tracking,
Super-resolution reconstruction
BibRef
Li, Z.,
Wang, Q.,
Gao, J.,
Li, B.,
Hu, W.,
End-to-End Temporal Feature Aggregation for Siamese Trackers,
ICIP20(2056-2060)
IEEE DOI
2011
Feature extraction, Target tracking, Proposals, Object tracking,
Training, Modulation, Visual object tracking, siamese network,
adversarial training
BibRef
Dasari, M.M.,
Gorthi, R.K.S.S.,
IOU: Siamtrack: IOU Guided Siamese Network For Visual Object Tracking,
ICIP20(2061-2065)
IEEE DOI
2011
Training, Visualization, Object tracking, Proposals, Target tracking,
Feature extraction, Testing, visual object tracking,
region proposals
BibRef
Guo, Q.[Qing],
Xie, X.F.[Xiao-Fei],
Juefei-Xu, F.[Felix],
Ma, L.[Lei],
Li, Z.G.[Zhong-Guo],
Xue, W.L.[Wan-Li],
Feng, W.[Wei],
Liu, Y.[Yang],
Spark: Spatial-aware Online Incremental Attack Against Visual Tracking,
ECCV20(XXV:202-219).
Springer DOI
2011
BibRef
Liang, S.Y.[Si-Yuan],
Wei, X.X.[Xing-Xing],
Yao, S.Y.[Si-Yuan],
Cao, X.C.[Xiao-Chun],
Efficient Adversarial Attacks for Visual Object Tracking,
ECCV20(XXVI:34-50).
Springer DOI
2011
BibRef
Dong, X.P.[Xing-Ping],
Shen, J.B.[Jian-Bing],
Shao, L.[Ling],
Porikli, F.M.[Fatih M.],
Clnet: A Compact Latent Network for Fast Adjusting Siamese Trackers,
ECCV20(XX:378-395).
Springer DOI
2011
BibRef
Przewlocka, D.[Dominika],
Wasala, M.[Mateusz],
Szolc, H.[Hubert],
Blachut, K.[Krzysztof],
Kryjak, T.[Tomasz],
Optimisation of a Siamese Neural Network for Real-time Energy Efficient
Object Tracking,
ICCVG20(151-163).
Springer DOI
2009
BibRef
Kretz, A.,
Mester, R.,
A Shared Representation for Object Tracking and Classification using
Siamese Networks,
SSIAI20(54-57)
IEEE DOI
2009
feature extraction, image classification, image representation,
neural nets, object tracking, Siamese network tracker,
object tracking
BibRef
Yu, Y.,
Xiong, Y.,
Huang, W.,
Scott, M.R.,
Deformable Siamese Attention Networks for Visual Object Tracking,
CVPR20(6727-6736)
IEEE DOI
2008
Target tracking, Visualization, Object tracking, Correlation,
Proposals, Task analysis, Convolution
BibRef
Chen, Z.,
Zhong, B.,
Li, G.,
Zhang, S.,
Ji, R.,
Siamese Box Adaptive Network for Visual Tracking,
CVPR20(6667-6676)
IEEE DOI
2008
Visualization, Target tracking, Adaptive systems, Detectors,
Convolution, Feature extraction
BibRef
Guo, D.,
Wang, J.,
Cui, Y.,
Wang, Z.,
Chen, S.,
SiamCAR: Siamese Fully Convolutional Classification and Regression
for Visual Tracking,
CVPR20(6268-6276)
IEEE DOI
2008
Feature extraction, Visualization, Target tracking, Proposals,
Training, Task analysis, Correlation
BibRef
Rout, L.[Litu],
Raju, P.M.[Priya Mariam],
Mishra, D.[Deepak],
Subrahmanyam, G.R.K.S.[Gorthi Rama Krishna Sai],
Learning Rotation Adaptive Correlation Filters in Robust Visual Object
Tracking,
ACCV18(II:646-661).
Springer DOI
1906
BibRef
Rout, L.[Litu],
Siddhartha,
Mishra, D.[Deepak],
Subrahmanyam, G.R.K.S.[Gorthi Rama Krishna Sai],
Rotation Adaptive Visual Object Tracking with Motion Consistency,
WACV18(1047-1055)
IEEE DOI
1806
convolution, feature selection, feedforward neural nets,
image capture, image motion analysis, image sequences,
Visualization
BibRef
Wang, L.[Li],
Pham, N.T.[Nam Trung],
Ng, T.T.[Tian-Tsong],
Wang, G.[Gang],
Chan, K.L.[Kap Luk],
Leman, K.[Karianto],
Learning Deep Features for Multiple Object Tracking by Using a
Multi-Task Learning Strategy,
ICIP14(838-842)
IEEE DOI
1502
Adaptation models
BibRef
Tan, W.R.,
Lai, S.,
i-Siam: Improving Siamese Tracker with Distractors Suppression and
Long-Term Strategies,
VisDrone19(55-63)
IEEE DOI
2004
feature extraction, image denoising, image segmentation,
neural nets, improving Siamese Tracker, distractors suppression,
Long term Tracking
BibRef
Wang, N.[Ning],
Song, Y.B.[Yi-Bing],
Ma, C.[Chao],
Zhou, W.[Wengang],
Liu, W.[Wei],
Li, H.Q.A.[Hou-Qi-Ang],
Unsupervised Deep Tracking,
CVPR19(1308-1317).
IEEE DOI
2002
BibRef
Li, X.[Xin],
Ma, C.[Chao],
Wu, B.Y.[Bao-Yuan],
He, Z.Y.[Zhen-Yu],
Yang, M.H.[Ming-Hsuan],
Target-Aware Deep Tracking,
CVPR19(1369-1378).
IEEE DOI
2002
BibRef
Giancola, S.[Silvio],
Zarzar, J.[Jesus],
Ghanem, B.[Bernard],
Leveraging Shape Completion for 3D Siamese Tracking,
CVPR19(1359-1368).
IEEE DOI
2002
BibRef
Li, B.[Bo],
Wu, W.[Wei],
Wang, Q.A.[Qi-Ang],
Zhang, F.Y.[Fang-Yi],
Xing, J.L.[Jun-Liang],
Yan, J.[Junjie],
SiamRPN++: Evolution of Siamese Visual Tracking With Very Deep Networks,
CVPR19(4277-4286).
IEEE DOI
2002
BibRef
Sutanto, E.B.[Edward Budiman],
Lee, S.[Sukho],
Online Information Augmented SiamRPN,
CVS19(480-489).
Springer DOI
1912
Siamese network for tracking.
Two images to two identical artificial neural networks as the inputs
and find the target area based on the similarity measured by the
Siamese network.
BibRef
Che, M.Q.[Man-Qiang],
Wang, R.L.[Run-Ling],
Lu, Y.[Yan],
Li, Y.[Yan],
Zhi, H.[Hui],
Xiong, C.Z.[Chang-Zhen],
Channel Pruning for Visual Tracking,
VOT18(I:70-82).
Springer DOI
1905
BibRef
Zhai, M.Y.[Meng-Yao],
Chen, L.[Lei],
Mori, G.[Greg],
Roshtkhari, M.J.[Mehrsan Javan],
Deep Learning of Appearance Models for Online Object Tracking,
WiCV-E18(IV:681-686).
Springer DOI
1905
BibRef
Jung, I.[Ilchae],
Son, J.[Jeany],
Baek, M.[Mooyeol],
Han, B.H.[Bo-Hyung],
Real-Time MDNet,
ECCV18(II: 89-104).
Springer DOI
1810
multi-domain convolutional neural network for tracking.
BibRef
Zhou, H.Z.[Hui-Zhong],
Ummenhofer, B.[Benjamin],
Brox, T.[Thomas],
DeepTAM: Deep Tracking and Mapping,
ECCV18(XVI: 851-868).
Springer DOI
1810
BibRef
Wang, G.,
Liu, B.,
Li, W.,
Yu, N.,
Flow Guided Siamese Network for Visual Tracking,
ICIP18(231-235)
IEEE DOI
1809
Target tracking, Visualization, Optical imaging, Benchmark testing,
Prediction algorithms, Optical propagation, Siamese-network,
deep learning
BibRef
Kokul, T.,
Fookes, C.,
Sridharan, S.,
Ramanan, A.,
Pinidiyaarachchi, U.A.J.,
Gate connected convolutional neural network for object tracking,
ICIP17(2602-2606)
IEEE DOI
1803
Adaptation models, Logic gates, Machine learning,
Network architecture, Object tracking, Target tracking,
object tracking
BibRef
Chakrabory, A.[Anit],
Dutta, S.[Sayandip],
A Machine Learning Inspired Approach for Detection, Recognition and
Tracking of Moving Objects from Real-Time Video,
PReMI17(170-178).
Springer DOI
1711
BibRef
Song, Y.,
Ma, C.,
Gong, L.,
Zhang, J.,
Lau, R.W.H.,
Yang, M.H.,
CREST: Convolutional Residual Learning for Visual Tracking,
ICCV17(2574-2583)
IEEE DOI
1802
convolution, feature extraction,
learning (artificial intelligence), neural nets, object tracking,
Visualization
BibRef
Guo, Q.,
Feng, W.,
Zhou, C.,
Huang, R.,
Wan, L.,
Wang, S.,
Learning Dynamic Siamese Network for Visual Object Tracking,
ICCV17(1781-1789)
IEEE DOI
1802
feature extraction, image classification, image representation,
image sequences, learning (artificial intelligence),
Visualization
BibRef
Serratosa, F.[Francesc],
Amézquita Gómez, N.[Nicolás],
Alquézar, R.[René],
Combining Neural Networks and Clustering Techniques for Object
Recognition in Indoor Video Sequences,
CIARP06(399-405).
Springer DOI
0611
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Target Tracking Techniques, Motion Model, Control .