16.7.4.4.2 Tracking Several People, Occlusions

Chapter Contents (Back)
Motion, Human. Tracking. Re-Identification. See also Tracking People, Re-Identification Issues, Occlusions. See also Tracking People with Stereo, or Depth. Learning, CNN, etc.: See also Tracking People, Re-Identification Issues, Learning.

Rigoll, G.[Gerhard], Breit, H.[Harald], Wallhoff, F.[Frank],
Robust tracking of persons in real-world scenarios using a statistical computer vision approach,
IVC(22), No. 7, July 2004, pp. 571-582.
Elsevier DOI 0405
BibRef

Rigoll, G.[Gerhard], Winterstein, B., Müller, S.[Stefan],
Robust Person Tracking in Real Scenarios with Non-Stationary Background Using a Statistical Computer Vision Approach,
VS99(xx-yy). BibRef 9900
And: A1, A3, A2:
Robust Person Tracking with Non-Stationary Background Using a Combined Pseudo-2D-HMM and Kalman-Filter Approach,
ICIP99(IV:242-246).
IEEE DOI BibRef

Rigoll, G.[Gerhard], Eickeler, S.[Stefan], Müller, S.[Stefan],
Person Tracking in Real-World Scenarios Using Statistical Methods,
AFGR00(342-347).
IEEE DOI 0003
BibRef
And: A3, A2, A1:
Crane Gesture Recognition using Pseudo 3-D Hidden Markov Models,
AFGR00(398-402).
IEEE DOI 0003
BibRef
Earlier: A3, A2, A1:
Pseudo 3-D HMMs for Image Sequence Recognition,
ICIP99(IV:237-241).
IEEE DOI BibRef

Eickeler, S.[Stefan], Rigoll, G.[Gerhard],
Hidden Markov Model Based Continuous Online Gesture Recognition,
ICPR98(Vol II: 1206-1208).
IEEE DOI 9808
BibRef

Breit, H., Rigoll, G.,
A flexible multimodal object tracking system,
ICIP03(III: 133-136).
IEEE DOI 0312
BibRef
Earlier:
Improved Person Tracking Using a Combined Pseudo-2D-HMM and Kalman Filter Approach with Automatic Background State Adaptation,
ICIP01(II: 53-56).
IEEE DOI 0108
Sports? BibRef

Wachter, S., Nagel, H.H.,
Tracking Persons in Monocular Image Sequences,
CVIU(74), No. 3, June 1999, pp. 174-192.
DOI Link BibRef 9906

Brill, F.Z.[Frank Z.], Olson, T.J.[Thomas J.],
Method of dealing with occlusion when tracking multiple objects and people in video sequences,
US_Patent6,542,621, Apr 1, 2003
WWW Link. BibRef 0304

Lerdsudwichai, C.[Charay], Abdel-Mottaleb, M.[Mohamed], Ansari, A.N.[A-Nasser],
Tracking multiple people with recovery from partial and total occlusion,
PR(38), No. 7, July 2005, pp. 1059-1070.
Elsevier DOI 0505
BibRef

Kang, H.G.[Hee-Gu], Kim, D.J.[Dai-Jin],
Real-time multiple people tracking using competitive condensation,
PR(38), No. 7, July 2005, pp. 1045-1058.
Elsevier DOI 0505
BibRef
Earlier: Add A3: Bang, S.Y.[Sung Yang], ICPR02(I: 413-416).
IEEE DOI 0211
BibRef
And: ICIP02(III: 325-328).
IEEE DOI 0210
BibRef

Khan, Z.[Zia], Balch, T.[Tucker], Dellaert, F.[Frank],
MCMC-Based Particle Filtering for Tracking a Variable Number of Interacting Targets,
PAMI(27), No. 11, November 2005, pp. 1805-1918.
IEEE DOI 0510
BibRef
Earlier:
A Rao-Blackwellized particle filter for eigentracking,
CVPR04(II: 980-986).
IEEE DOI 0408
BibRef
And:
An MCMC-Based Particle Filter for Tracking Multiple Interacting Targets,
ECCV04(Vol IV: 279-290).
Springer DOI 0405
Markov-Chain Monte Carlo. Deal with problems that arise when the tracking is lost. See also EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation. BibRef

Lanz, O.[Oswald],
Approximate Bayesian Multibody Tracking,
PAMI(28), No. 9, September 2006, pp. 1436-1449.
IEEE DOI 0608
BibRef

Lanz, O.[Oswald], Manduchi, R.[Roberto],
Hybrid Joint-Separable Multibody Tracking,
CVPR05(I: 413-420).
IEEE DOI 0507
BibRef

Lanz, O.[Oswald], Hu, T.[Tao],
Dynamic resource allocation for probabilistic tracking via attentive sensing and sampling,
RAWNETS11(432-434).
IEEE DOI 1111
BibRef

Rui, Y.[Yong], Chen, Y.Q.[Yun-Qiang],
Automatic detection and tracking of multiple individuals using multiple cues,
US_Patent7,130,446, Oct 31, 2006
WWW Link. BibRef 0610
And: US_Patent7,151,843, Dec 19, 2006
WWW Link. BibRef
And: US_Patent7,171,025, Jan 30, 2007
WWW Link. BibRef
And: US_Patent7,428,315, Sep 23, 200
WWW Link. BibRef

Zhao, T.[Tao], Aggarwal, M.[Manoj], Germano, T.[Thomas], Roth, I.[Ian], Knowles, A.[Alexandar], Kumar, R.[Rakesh], Sawhney, H.[Harpreet], Samarasekera, S.[Supun],
Toward a sentient environment: Real-time wide area multiple human tracking with identities,
MVA(19), No. 5-6, October 2008, pp. xx-yy.
Springer DOI 0810
BibRef

Min, J.H.[Jung-Hye], Kasturi, R.[Rangachar], Camps, O.I.[Octavia I.],
Extraction and Temporal Segmentation of Multiple Motion Trajectories in Human Motion,
IVC(26), No. 12, 1 December 2008, pp. 1621-1635.
Elsevier DOI 0810
BibRef
Earlier: A1, A2, Only: EventVideo04(118).
IEEE DOI 0502
Activity recognition; Motion trajectories; Motion tracking; Motion segmentation; Motion detection; Temporal segmentation BibRef

Min, J.H.[Jung-Hye], Park, J.H.[Jin Hyeong], Kasturi, R.[Rangachar],
Extraction of Multiple Motion Trajectories in Human Motion,
SCIA03(1050-1057).
Springer DOI 0310
BibRef

Wang, J.[Jing], Yin, Y.F.[Ya-Feng], Man, H.[Hong],
Multiple Human Tracking Using Particle Filter with Gaussian Process Dynamical Model,
JIVP(2008), No. 2008, pp. xx-yy.
DOI Link 0804
BibRef
And: A1, A3, A2:
Tracking human body by using particle filter Gaussian process Markov-switching model,
ICPR08(1-4).
IEEE DOI 0812
BibRef
Earlier: A1, A3, A2:
Multitarget tracking using Gaussian Process Dynamical Model particle filter,
ICIP08(1580-1583).
IEEE DOI 0810
BibRef

Yin, Y.F.[Ya-Feng], Man, H.[Hong], Wang, J.[Jing], Yang, G.[Guang],
Human Motion Change Detection by Hierarchical Gaussian Process Dynamical Model with Particle Filter,
AVSS10(307-314).
IEEE DOI 1009
BibRef

Hu, W.M.[Wei-Ming], Zhou, X.[Xue], Hu, M.[Min], Maybank, S.J.[Steve J.],
Occlusion Reasoning for Tracking Multiple People,
CirSysVideo(19), No. 1, January 2009, pp. 114-121.
IEEE DOI 0902
BibRef

Wang, K., Ding, C., Maybank, S.J., Tao, D.,
CDPM: Convolutional Deformable Part Models for Semantically Aligned Person Re-Identification,
IP(29), 2020, pp. 3416-3428.
IEEE DOI 2002
Person re-identification, alignment-robust recognition, part-based model, multi-task learning BibRef

Ma, Y.Q.[Yun-Qian], Yu, Q.[Qian], Cohen, I.[Isaac],
Target tracking with incomplete detection,
CVIU(113), No. 4, April 2009, pp. 580-587.
Elsevier DOI 0903
BibRef
Earlier:
Multiple Hypothesis Target Tracking Using Merge and Split of Graph's Nodes,
ISVC06(I: 783-792).
Springer DOI
PDF File. 0611
Multiple target tracking; Split and merge of detected regions; Maximum a posteriori BibRef

Yu, Q.[Qian], Medioni, G.[Gerard],
Multiple-Target Tracking by Spatiotemporal Monte Carlo Markov Chain Data Association,
PAMI(31), No. 12, December 2009, pp. 2196-2210.
IEEE DOI 0911
BibRef
Earlier:
Integrated Detection and Tracking for Multiple Moving Objects using Data-Driven MCMC Data Association,
Motion08(1-8).
IEEE DOI
PDF File. 0801
BibRef
Earlier:
Map-Enhanced Detection and Tracking from a Moving Platform with Local and Global Data Association,
Motion07(3-3).
IEEE DOI
PDF File. 0702
Apply espceciall to people tracking, but also vehicles. BibRef

Dinh, T.B.[Thang Ba], Vo, N.N.[Nam N.], Medioni, G.[Gerard],
Context tracker: Exploring supporters and distracters in unconstrained environments,
CVPR11(1177-1184).
IEEE DOI 1106
BibRef

Dinh, T.B.[Thang Ba], Vo, N.N.[Nam N.], Medioni, G.[Gerard],
High resolution face sequences from a PTZ network camera,
FG11(531-538).
IEEE DOI 1103
BibRef

Cai, Y.H.[Ying-Hao], Medioni, G.[Gérard],
Persistent people tracking and face capture using a PTZ camera,
MVA(27), No. 3, April 2016, pp. 397-413.
Springer DOI 1604
BibRef
Earlier: A2, A1:
Persistent People Tracking and Face Capture over a Wide Area,
LTDT14(714-715)
IEEE DOI 1409
BibRef
Earlier: A1, A2:
Exploring context information for inter-camera multiple target tracking,
WACV14(761-768)
IEEE DOI 1406
Cameras; Color; Context;Histograms; Image color analysis; Target tracking BibRef

Cai, Y.H.[Ying-Hao], Medioni, G., Dinh, T.B.[Thang Ba],
Towards a practical PTZ face detection and tracking system,
WACV13(31-38).
IEEE DOI 1303
BibRef

Dinh, T.B.[Thang Ba], Medioni, G.[Gerard],
Co-training framework of generative and discriminative trackers with partial occlusion handling,
WMVC11(642-649).
IEEE DOI 1101
BibRef

Dinh, T.B.[Thang Ba], Yu, Q.[Qian], Medioni, G.[Gérard],
Real time tracking using an active pan-tilt-zoom network camera,
IROS09(3786-3793).
PDF File. BibRef 0900

Yu, Q.[Qian], Dinh, T.B.[Thang Ba], Medioni, G.[Gérard],
Online Tracking and Reacquisition Using Co-trained Generative and Discriminative Trackers,
ECCV08(II: 678-691).
Springer DOI 0810
BibRef

Yu, Q.[Qian], Medioni, G.[Gerard], Cohen, I.[Isaac],
Multiple Target Tracking Using Spatio-Temporal Markov Chain Monte Carlo Data Association,
CVPR07(1-8).
IEEE DOI
PDF File. 0706
BibRef

Yu, Q.[Qian], Cohen, I.[Isaac], Medioni, G.[Gerard], Wu, B.[Bo],
Boosted Markov Chain Monte Carlo Data Association for Multiple Target Detection and Tracking,
ICPR06(II: 675-678).
IEEE DOI
PDF File. 0609
BibRef

Piotto, N.[Nicola], Conci, N.[Nicola], de Natale, F.G.B.[Francesco G.B.],
Syntactic Matching of Trajectories for Ambient Intelligence Applications,
MultMed(11), No. 7, November 2009, pp. 1266-1275.
IEEE DOI 0911
BibRef
And: A1, A3, A2:
Hierarchical Matching of 3D Pedestrian Trajectories for Surveillance Applications,
AVSBS09(146-151).
IEEE DOI 0909
BibRef

Sherrah, J.[Jamie], Ristic, B.[Branko], Redding, N.J.[Nicholas J.],
Particle filter to track multiple people for visual surveillance,
IET-CV(5), No. 4, 2011, pp. 192-200.
DOI Link 1107
BibRef
Earlier:
Evaluation of a Particle Filter to Track People for Visual Surveillance,
DICTA09(96-102).
IEEE DOI 0912
See also Online Tracking of People through a Camera Network. BibRef

de Laet, T.[Tinne], Bruyninckx, H.[Herman], de Schutter, J.[Joris],
Shape-Based Online Multitarget Tracking and Detection for Targets Causing Multiple Measurements: Variational Bayesian Clustering and Lossless Data Association,
PAMI(33), No. 12, December 2011, pp. 2477-2491.
IEEE DOI 1110
Multiple measurements for target. High level target position and shape, low-level clusters of measurements. Apply to video and laser date for tracking people and ants. BibRef

Huo, F.F.[Fei-Fei], Hendriks, E.A.[Emile A.],
Multiple people tracking and pose estimation with occlusion estimation,
CVIU(116), No. 5, May 2012, pp. 634-647.
Elsevier DOI 1203
Multiple people tracking; Pose estimation; Occlusion estimation BibRef

Li, L., Yan, S., Yu, X., Tan, Y.K., Li, H.,
Robust Multiperson Detection and Tracking for Mobile Service and Social Robots,
SMC-B(42), No. 5, October 2012, pp. 1398-1412.
IEEE DOI 1209
BibRef

Shen, Y.[Yuan], Miao, Z.J.[Zhen-Jiang],
Multi-human tracking from sparse detection responses,
IET-CV(6), No. 6, 2012, pp. 590-602.
DOI Link 1301
BibRef

Shen, Y.[Yuan], Miao, Z.J.[Zhen-Jiang], Wang, Z.F.[Zhi-Fei],
A cost function approach for multi-human tracking,
ICIP11(481-484).
IEEE DOI 1201
BibRef

Yamasaki, T.[Toshihiko], Matsunami, T.[Tomoaki], Chen, T.[Tuhan],
Human Attribute Analysis Using a Top-View Camera Based on Two-Stage Classification,
IEICE(E96-D), No. 4, April 2013, pp. 993-996.
WWW Link. 1304
BibRef
Earlier: A1, A2, Only:
Pedestrian Attribute Analysis Using a Top-View Camera in a Public Space,
MMMod12(541-550).
Springer DOI 1201
BibRef

Sun, L.[Li], Liu, G.Z.[Gui-Zhong], Liu, Y.Q.[Yi-Qing],
Multiple pedestrians tracking algorithm by incorporating histogram of oriented gradient detections,
IET-IPR(7), No. 7, October 2013, pp. 653-659.
DOI Link 1312
gradient methods BibRef

Brscic, D., Kanda, T., Ikeda, T., Miyashita, T.,
Person Tracking in Large Public Spaces Using 3-D Range Sensors,
HMS(43), No. 6, 2013, pp. 522-534.
IEEE DOI 1312
Cameras BibRef

Cancela, B., Ortega, M., Penedo, M.G.,
Multiple human tracking system for unpredictable trajectories,
MVA(25), No. 2, February 2014, pp. 511-527.
WWW Link. 1402
BibRef

Shen, Y.[Yuan], Miao, Z.J.[Zhen-Jiang],
Multihuman Tracking Based on a Spatial-Temporal Appearance Match,
CirSysVideo(24), No. 3, March 2014, pp. 361-373.
IEEE DOI 1404
Bayes methods BibRef

Lee, D.H.[Dong-Hoon], Hwang, I.[Inhwan], Oh, S.H.[Song-Hwai],
OPTIMUS: Online Persistent Tracking and Identification of Many Users for Smart Spaces,
MVA(25), No. 4, May 2014, pp. 901-917.
WWW Link. 1404
BibRef

Wang, L.[Lu], Yung, N.H.C.[Nelson H.C.], Xu, L.S.[Li-Sheng],
Multiple-Human Tracking by Iterative Data Association and Detection Update,
ITS(15), No. 5, October 2014, pp. 1886-1899.
IEEE DOI 1410
BibRef
Earlier: A1, A2, Only:
Detection Based Low Frame Rate Human Tracking,
ICPR10(3529-3532).
IEEE DOI 1008
feature extraction BibRef

Peng, P.X.[Pei-Xi], Tian, Y.H.[Yong-Hong], Wang, Y.W.[Yao-Wei], Li, J.[Jia], Huang, T.J.[Tie-Jun],
Robust multiple cameras pedestrian detection with multi-view Bayesian network,
PR(48), No. 5, 2015, pp. 1760-1772.
Elsevier DOI 1502
BibRef
Earlier: A1, A2, A3, A5, Only:
Multi-camera Pedestrian Detection with Multi-view Bayesian Network Model,
BMVC12(69).
DOI Link 1301
Pedestrian detection BibRef

Xu, T.[Teng], Peng, P.X.[Pei-Xi], Fang, X.Y.[Xiao-Yu], Su, C.[Chi], Wang, Y.W.[Yao-Wei], Tian, Y.H.[Yong-Hong], Zeng, W.[Wei], Huang, T.J.[Tie-Jun],
Single and Multiple View Detection, Tracking and Video Analysis in Crowded Environments,
AVSS12(494-499).
IEEE DOI 1211
BibRef

Chen, L.[Lili], Wang, W.[Wei], Panin, G., Knoll, A.,
Hierarchical Grid-based Multi-People Tracking-by-Detection With Global Optimization,
IP(24), No. 11, November 2015, pp. 4197-4212.
IEEE DOI 1509
image sequences BibRef

McLaughlin, N.[Niall], del Rincon, J.M.[Jesus Martinez], Miller, P.[Paul],
Dense Multiperson Tracking with Robust Hierarchical Linear Assignment,
Cyber(45), No. 7, July 2015, pp. 1276-1288.
IEEE DOI 1506
BibRef
Earlier:
Enhancing Linear Programming with Motion Modeling for Multi-target Tracking,
WACV15(71-77)
IEEE DOI 1503
BibRef
Earlier:
Online multiperson tracking with occlusion reasoning and unsupervised track motion model,
AVSS13(37-42)
IEEE DOI 1311
Cost function. Detectors Computational modeling BibRef

Li, Y.[Yuke], Shen, W.M.[Wei-Ming],
Inter-Person Occlusion Handling with Social Interaction for Online Multi-Pedestrian Tracking,
IEICE(E99-D), No. 12, December 2016, pp. 3165-3171.
WWW Link. 1612
BibRef
Earlier:
Social interaction based handling inter-person occlusion for online multi-pedestrian tracking,
AVSS15(1-6)
IEEE DOI 1511
image motion analysis BibRef

Ba, S.O.[Sileye O.], Alameda-Pineda, X.[Xavier], Xompero, A.[Alessio], Horaud, R.[Radu],
An on-line variational Bayesian model for multi-person tracking from cluttered scenes,
CVIU(153), No. 1, 2016, pp. 64-76.
Elsevier DOI 1612
Multi-person tracking BibRef

Ban, Y.T.[Yu-Tong], Ba, S.O.[Sileye O.], Alameda-Pineda, X.[Xavier], Horaud, R.[Radu],
Tracking Multiple Persons Based on a Variational Bayesian Model,
MOTC16(II: 52-67).
Springer DOI 1611
BibRef

Babaee, M., You, Y., Rigoll, G.[Gerhard],
Combined segmentation, reconstruction, and tracking of multiple targets in multi-view video sequences,
CVIU(154), No. 1, 2017, pp. 166-181.
Elsevier DOI 1612
Superpixels BibRef

Hofmann, M.[Martin], Haag, M., Rigoll, G.[Gerhard],
Unified hierarchical multi-object tracking using global data association,
PETS13(22-28)
IEEE DOI 1411
data handling BibRef

Hofmann, M.[Martin], Wolf, D.[Daniel], Rigoll, G.[Gerhard],
Hypergraphs for Joint Multi-view Reconstruction and Multi-object Tracking,
CVPR13(3650-3657)
IEEE DOI 1309
hypergraphs; multi-object; multi-view; surveillance; tracking BibRef

Hofmann, M.[Martin], Rigoll, G.[Gerhard], Huang, T.S.[Thomas S.],
Dense spatio-temporal motion segmentation for tracking multiple self-occluding people,
SISM10(9-14).
IEEE DOI 1006
BibRef

Wang, B.[Bing], Wang, G.[Gang], Chan, K.L.[Kap Luk], Wang, L.[Li],
Tracklet Association by Online Target-Specific Metric Learning and Coherent Dynamics Estimation,
PAMI(39), No. 3, March 2017, pp. 589-602.
IEEE DOI 1702
BibRef
Earlier:
Tracklet Association with Online Target-Specific Metric Learning,
CVPR14(1234-1241)
IEEE DOI 1409
Dynamics. long-term multi-person tracking. BibRef

Das, A.[Abir], Panda, R.[Rameswar], Roy-Chowdhury, A.K.[Amit K.],
Continuous adaptation of multi-camera person identification models through sparse non-redundant representative selection,
CVIU(156), No. 1, 2017, pp. 66-78.
Elsevier DOI 1702
BibRef
Earlier:
Active image pair selection for continuous person re-identification,
ICIP15(4263-4267)
IEEE DOI 1512
Redundancy reduction. Active learning; Attributes; Person re-identification BibRef

Ma, X.L.[Xiao-Long], Zhu, X.T.[Xia-Tian], Gong, S.G.[Shao-Gang], Xie, X.D.[Xu-Dong], Hu, J.M.[Jian-Ming], Lam, K.M.[Kin-Man], Zhong, Y.S.[Yi-Sheng],
Person re-identification by unsupervised video matching,
PR(65), No. 1, 2017, pp. 197-210.
Elsevier DOI 1702
Person re-identification BibRef

Li, W.[Wei], Zhu, X.T.[Xia-Tian], Gong, S.G.[Shao-Gang],
Scalable Person Re-Identification by Harmonious Attention,
IJCV(128), No. 6, June 2020, pp. 1635-1653.
Springer DOI 2006
BibRef

Li, M.X.[Min-Xian], Zhu, X.T.[Xia-Tian], Gong, S.G.[Shao-Gang],
Unsupervised Tracklet Person Re-Identification,
PAMI(42), No. 7, July 2020, pp. 1770-1782.
IEEE DOI 2006
Cameras, Data models, Deep learning, Labeling, Adaptation models, Unsupervised learning, Training data, Person re-identification, multi-task deep learning BibRef

Wu, L.[Lin], Shen, C.H.[Chun-Hua], van den Hengel, A.J.[Anton J.],
Deep linear discriminant analysis on fisher networks: A hybrid architecture for person re-identification,
PR(65), No. 1, 2017, pp. 238-250.
Elsevier DOI 1702
Linear discriminant analysis BibRef

Karanam, S.[Srikrishna], Li, Y.[Yang], Radke, R.J.[Richard J.],
Person re-identification with block sparse recovery,
IVC(60), No. 1, 2017, pp. 75-90.
Elsevier DOI 1704
BibRef
Earlier:
Particle dynamics and multi-channel feature dictionaries for robust visual tracking,
BMVC15(xx-yy).
DOI Link 1601
Person re-identification BibRef

Karanam, S.[Srikrishna], Gou, M.R.[Meng-Ran], Wu, Z.Y.[Zi-Yan], Rates-Borras, A.[Angels], Camps, O.I.[Octavia I.], Radke, R.J.[Richard J.],
A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets,
PAMI(41), No. 3, March 2019, pp. 523-536.
IEEE DOI 1902
Feature extraction, Measurement, Cameras, Benchmark testing, Probes, Image color analysis, Histograms, Person re-identification, benchmark BibRef

Zheng, M., Karanam, S.[Srikrishna], Radke, R.J.[Richard J.],
RPIfield: A New Dataset for Temporally Evaluating Person Re-identification,
WiCV18(1974-19742)
IEEE DOI 1812
Cameras, Probes, Benchmark testing, Measurement, Conferences, Economic indicators, Legged locomotion BibRef

Narayan, N., Sankaran, N., Setlur, S., Govindaraju, V.,
Re-identification for Online Person Tracking by Modeling Space-Time Continuum,
Joint18(1519-151909)
IEEE DOI 1812
Cameras, Feature extraction, Target tracking, Logic gates, Trajectory, Hidden Markov models BibRef

Madrigal, F.[Francisco], Hayet, J.B.[Jean-Bernard], Rivera, M.[Mariano],
Motion priors for multiple target visual tracking,
MVA(26), No. 2-3, April 2015, pp. 141-160.
WWW Link. 1504
BibRef
Earlier: A1, A3, A2:
Learning and Regularizing Motion Models for Enhancing Particle Filter-Based Target Tracking,
PSIVT11(II: 287-298).
Springer DOI 1111
See also Evaluation of multiple motion models for multiple pedestrian visual tracking. BibRef

Madrigal, F.[Francisco], Hayet, J.B.[Jean-Bernard],
Motion priors based on goals hierarchies in pedestrian tracking applications,
MVA(28), No. 3-4, May 2017, pp. 341-359.
WWW Link. 1704
BibRef
Earlier:
Evaluation of multiple motion models for multiple pedestrian visual tracking,
AVSS13(31-36)
IEEE DOI 1311
BibRef
Earlier:
Multiple view, multiple target tracking with principal axis-based data association,
AVSBS11(185-190).
IEEE DOI 1111
Bayes methods See also Learning and Regularizing Motion Models for Enhancing Particle Filter-Based Target Tracking. BibRef

Jia, J.[Jieru], Ruan, Q.Q.[Qiu-Qi], An, G.[Gaoyun], Jin, Y.[Yi],
Multiple metric learning with query adaptive weights and multi-task re-weighting for person re-identification,
CVIU(160), No. 1, 2017, pp. 87-99.
Elsevier DOI 1706
Person re-identification BibRef

Zhao, C.R.[Cai-Rong], Wang, X.K.[Xue-Kuan], Wong, W.K.[Wai Keung], Zheng, W.S.[Wei-Shi], Yang, J.[Jian], Miao, D.Q.[Duo-Qian],
Multiple metric learning based on bar-shape descriptor for person re-identification,
PR(71), No. 1, 2017, pp. 218-234.
Elsevier DOI 1707
Person, re-identification BibRef

Yin, J.H.[Jia-Hang], Wu, A.[Ancong], Zheng, W.S.[Wei-Shi],
Fine-Grained Person Re-identification,
IJCV(128), No. 6, June 2020, pp. 1654-1672.
Springer DOI 2006
BibRef

Zhu, X., Wu, B., Huang, D., Zheng, W.S.,
Fast Open-World Person Re-Identification,
IP(27), No. 5, May 2018, pp. 2286-2300.
IEEE DOI 1804
image matching, image representation, learning (artificial intelligence), open search space BibRef

Zhang, Z.Y.[Zong-Yan], Zhao, C.R.[Cai-Rong], Miao, D.Q.[Duo-Qian], Wang, X.[Xuekuan], Lai, Z.H.[Zhi-Hui], Yang, J.[Jian],
Saliency-Based Person Re-identification by Probability Histogram,
HIS16(III: 315-329).
Springer DOI 1704
BibRef

Wu, L.[Lin], Wang, Y.[Yang], Gao, J.B.[Jun-Bin], Li, X.[Xue],
Deep adaptive feature embedding with local sample distributions for person re-identification,
PR(73), No. 1, 2018, pp. 275-288.
Elsevier DOI 1709
Deep feature embedding BibRef

Wu, L.[Lin], Wang, Y.[Yang], Ge, Z.Y.[Zong-Yuan], Hu, Q.C.[Qi-Chang], Li, X.[Xue],
Structured deep hashing with convolutional neural networks for fast person re-identification,
CVIU(167), 2018, pp. 63-73.
Elsevier DOI 1804
Person re-identification, Convolutional neural networks, Deep hashing, Structured embedding BibRef

Wu, L.[Lin], Wang, Y.[Yang], Li, X.[Xue], Gao, J.B.[Jun-Bin],
What-and-where to match: Deep spatially multiplicative integration networks for person re-identification,
PR(76), No. 1, 2018, pp. 727-738.
Elsevier DOI 1801
Multiplicative integration gating BibRef

Li, S.Q.[Shuang-Qun], Ma, H.D.[Hua-Dong],
A Siamese inception architecture network for person re-identification,
MVA(28), No. 7, October 2017, pp. 725-736.
WWW Link. 1710
BibRef

Zhao, Z.C.[Zhi-Cheng], Zhao, B.L.[Bin-Lin], Su, F.[Fei],
Person re-identification via integrating patch-based metric learning and local salience learning,
PR(75), No. 1, 2018, pp. 90-98.
Elsevier DOI 1712
Person re-identification BibRef

Ren, Y.T.[Yu-Tao], Li, X.L.[Xue-Long], Lu, X.Q.[Xiao-Qiang],
Feedback mechanism based iterative metric learning for person re-identification,
PR(75), No. 1, 2018, pp. 99-111.
Elsevier DOI 1712
Person re-identification BibRef

Jiang, Z.Q.[Zheng-Qiang], Huynh, D.Q.[Du Q.],
Multiple Pedestrian Tracking From Monocular Videos in an Interacting Multiple Model Framework,
IP(27), No. 3, March 2018, pp. 1361-1375.
IEEE DOI 1801
Adaptation models, Computational modeling, Histograms, Image color analysis, Target tracking, Videos, Munkres' algorithm, visual tracking BibRef

Jiang, Z.Q.[Zheng-Qiang], Huynh, D.Q.[Du Q.], Moran, W.[William], Challa, S.[Subhash], Spadaccini, N.[Nick],
Multiple Pedestrian Tracking Using Colour and Motion Models,
DICTA10(328-334).
IEEE DOI 1012
BibRef

Jiang, Z.Q.[Zheng-Qiang], Huynh, D.Q.[Du Q.], Moran, W.[William], Challa, S.[Subhash],
Tracking pedestrians using smoothed colour histograms in an interacting multiple model framework,
ICIP11(2313-2316).
IEEE DOI 1201
BibRef

Zhou, S., Wang, J., Shi, R., Hou, Q., Gong, Y., Zheng, N.,
Large Margin Learning in Set-to-Set Similarity Comparison for Person Reidentification,
MultMed(20), No. 3, March 2018, pp. 593-604.
IEEE DOI 1802
Cameras, Feature extraction, Learning systems, Machine learning, Measurement, Neural networks, Robustness, Person re-identification, set to set similarity comparison BibRef

Lejbřlle, A.R.[Aske R.], Nasrollahi, K.[Kamal], Moeslund, T.B.[Thomas B.],
Enhancing person re-identification by late fusion of low-, mid- and high-level features,
IET-Bio(7), No. 2, March 2018, pp. 125-135.
DOI Link 1802
BibRef

Barbosa, I.B.[Igor Barros], Cristani, M.[Marco], Caputo, B.[Barbara], Rognhaugen, A.[Aleksander], Theoharis, T.[Theoharis],
Looking beyond appearances: Synthetic training data for deep CNNs in re-identification,
CVIU(167), 2018, pp. 50-62.
Elsevier DOI 1804
Re-identification, Deep learning, Training set, Automated training dataset generation, Re-identification photorealistic dataset BibRef

Tian, Y.[Ying], Zeng, M.Y.[Ming-Yong], Lu, A.[AiHong], Gao, B.[Bin], Luo, Z.K.[Zhang-Kai],
Improving Person Re-Identification by Efficient Pairwise-Specific CRC Coding in the XQDA Subspace,
IEICE(E101-D), No. 4, April 2018, pp. 1209-1212.
WWW Link. 1804
BibRef

Feng, Z., Lai, J., Xie, X.,
Learning View-Specific Deep Networks for Person Re-Identification,
IP(27), No. 7, July 2018, pp. 3472-3483.
IEEE DOI 1805
Benchmark testing, Cameras, Computational modeling, Dictionaries, Feature extraction, Machine learning, Measurement, view-specific deep networks BibRef

Chen, Y.[Ying], Yuan, J.[Jin], Li, Z.Y.[Zhi-Yong], Wu, Y.Q.[Yi-Qiang], Nouioua, M.[Mourad], Xie, G.[Guoqi],
Person re-identification based on re-ranking with expanded k-reciprocal nearest neighbors,
JVCIR(58), 2019, pp. 486-494.
Elsevier DOI 1901
Person re-identification, Re-ranking, Expanded k-reciprocal neighbors, Rank list similarity BibRef

Lv, J.Y.[Jing-Yi], Li, Z.Y.[Zhi-Yong], Nai, K.[Ke], Chen, Y.[Ying], Yuan, J.[Jin],
Person re-identification with expanded neighborhoods distance re-ranking,
IVC(95), 2020, pp. 103875.
Elsevier DOI 2004
Person re-identification, Re-ranking, Expanded neighborhoods distance, Two-level neighborhoods BibRef

Lisanti, G.[Giuseppe], Martinel, N.[Niki], Micheloni, C.[Christian], del Bimbo, A.[Alberto], Foresti, G.L.[Gian Luca],
From person to group re-identification via unsupervised transfer of sparse features,
IVC(83-84), 2019, pp. 29-38.
Elsevier DOI 1904
BibRef
Earlier: A1, A2, A4, A5, Only:
Group Re-identification via Unsupervised Transfer of Sparse Features Encoding,
ICCV17(2468-2477)
IEEE DOI 1802
Group Re-Identification, Dictionary learning, Encoding. feature extraction, group theory, image coding, image matching, image representation, image sensors, unsupervised learning, Re, Visualization BibRef

Martinel, N.[Niki], Foresti, G.L.[Gian Luca], Micheloni, C.[Christian],
Distributed person re-identification through network-wise rank fusion consensus,
PRL(124), 2019, pp. 63-73.
Elsevier DOI 1906
Re-Identification, Distributed, Camera network, Rank fusion, Consensus BibRef

Lu, J., He, Y., Liu, T., Chen, X.,
Centralized and Clustered Features for Person Re-Identification,
SPLetters(26), No. 6, June 2019, pp. 933-937.
IEEE DOI 1906
Feature extraction, Training, Reliability, Signal processing algorithms, Unsupervised learning, penalty term BibRef

Lei, J., Niu, L., Fu, H., Peng, B., Huang, Q., Hou, C.,
Person Re-Identification by Semantic Region Representation and Topology Constraint,
CirSysVideo(29), No. 8, August 2019, pp. 2453-2466.
IEEE DOI 1908
Measurement, Feature extraction, Semantics, Image color analysis, Reliability, Probes, Topology, Person re-identification, topological relationship BibRef

Wang, Z., Jiang, J., Yu, Y., Satoh, S.,
Incremental Re-Identification by Cross-Direction and Cross-Ranking Adaption,
MultMed(21), No. 9, September 2019, pp. 2376-2386.
IEEE DOI 1909
History, Cameras, Task analysis, Optimization, Trajectory, Video surveillance, Image retrieval, Person re-identification, log, cross-ranking BibRef

Baharani, M.[Mohammadreza], Mohan, S.[Shrey], Tabkhi, H.[Hamed],
Real-Time Person Re-identification at the Edge: A Mixed Precision Approach,
ICIAR19(II:27-39).
Springer DOI 1909
BibRef

Jiang, L., Liang, C., Xu, D., Huang, W.,
Multi-Similarity Re-Ranking for Person Re-Identification,
ICIP19(1212-1216)
IEEE DOI 1910
contextual similarity, graph-based similarity, re-ranking, diffusion, person re-identification BibRef

Lu, Y., Hong, Z., Liu, B., Li, W., Yu, N.,
Dhff: Robust Multi-Scale Person Search by Dynamic Hierarchical Feature Fusion,
ICIP19(3935-3939)
IEEE DOI 1910
Person Search, Person Re-Identification, Multi-Scale BibRef

Zhang, Y.S.[Yu-Sheng], Zhou, Z.H.[Zhi-Heng], Li, B.[Bo], Huang, Y.[Yu], Huang, J.C.[Jun-Chu], Chen, Z.Q.[Zeng-Qun],
Improving Slice-Based Model for Person Re-ID with Multi-Level Representation and Triplet-Center Loss,
IEICE(E102-D), No. 11, November 2019, pp. 2230-2237.
WWW Link. 1912
BibRef

Wang, J.B.[Jia-Bao], Li, Y.[Yang], Jiao, S.S.[Shan-Shan], Miao, Z.[Zhuang], Zhang, R.[Rui],
Grafted network for person re-identification,
SP:IC(80), 2020, pp. 115674.
Elsevier DOI 1912
Person re-identification, Feature representation, Multi-level feature, Part-based feature, Grafting BibRef

Kim, K.[Kikyung], Byeon, M.[Moonsub], Choi, J.Y.[Jin Young],
Re-ranking with ranking-reflected similarity for person re-identification,
PRL(128), 2019, pp. 326-332.
Elsevier DOI 1912
Person re-identification, Re-ranking, Similarity metric BibRef

Cheng, D.[De], Li, Z.H.[Zhi-Hui], Gong, Y.H.[Yi-Hong], Zhang, D.W.[Ding-Wen],
Fusion of Multiple Person Re-id Methods With Model and Data-Aware Abilities,
Cyber(50), No. 2, February 2020, pp. 561-571.
IEEE DOI 1912
Measurement, Task analysis, Robustness, Learning systems, Visualization, Benchmark testing, Computational modeling, Fusion, person reidentification (person re-id) BibRef

Liu, Z.[Zheng], Wang, Y.H.[Yun-Hong], Li, A.[Annan],
Hierarchical Integration of Rich Features for Video-Based Person Re-Identification,
CirSysVideo(29), No. 12, December 2019, pp. 3646-3659.
IEEE DOI 1912
Feature extraction, Legged locomotion, Semantics, Optical computing, Optical imaging, Visualization, multi-model ensemble BibRef

Cao, J., Pang, Y., Han, J., Gao, B., Li, X.,
Taking a Look at Small-Scale Pedestrians and Occluded Pedestrians,
IP(29), 2020, pp. 3143-3152.
IEEE DOI 2002
Small-scale pedestrians, occluded pedestrians, location bootstrap, semantic transition BibRef

Wang, F.[Fengyuan], Zhang, C.[Chi], Chen, S.[Shenghui], Ying, G.[Guode], Lv, J.H.[Jian-Hua],
Engineering Hand-designed and Deeply-learned features for person Re-identification,
PRL(130), 2020, pp. 293-298.
Elsevier DOI 2002
Deep feature, Hand-crafted, Multimodal feature fusion, Person re-identification BibRef

Zhang, S.[Shun], Huang, J.B.[Jia-Bin], Lim, J.W.[Jong-Woo], Gong, Y.H.[Yi-Hong], Wang, J.[Jinjun], Ahuja, N.[Narendra], Yang, M.H.[Ming-Hsuan],
Tracking Persons-of-Interest via Unsupervised Representation Adaptation,
IJCV(128), No. 1, January 2020, pp. 96-120.
Springer DOI 2002
BibRef
Earlier: A1, A3, A4, A2, A5, A6, A7:
Tracking Persons-of-Interest via Adaptive Discriminative Features,
ECCV16(V: 415-433).
Springer DOI 1611
BibRef

Wei, L.[Long], Wei, Z.Y.[Zhen-Yong], Jin, Z.M.[Zhong-Ming], Yu, Z.X.[Zheng-Xu], Huang, J.Q.[Jian-Qiang], Cai, D.[Deng], He, X.F.[Xiao-Fei], Hua, X.S.[Xian-Sheng],
SIF: Self-Inspirited Feature Learning for Person Re-Identification,
IP(29), 2020, pp. 4942-4951.
IEEE DOI 2003
Feature extraction, Training, Optimization, Task analysis, Computational modeling, Data mining, Semantics, image retrieval. BibRef

Wan, C.Q.[Chao-Qun], Wu, Y.[Yue], Tian, X.M.[Xin-Mei], Huang, J.Q.[Jian-Qiang], Hua, X.S.[Xian-Sheng],
Concentrated Local Part Discovery With Fine-Grained Part Representation for Person Re-Identification,
MultMed(22), No. 6, June 2020, pp. 1605-1618.
IEEE DOI 2005
Feature extraction, Visualization, Cameras, Convolutional neural networks, Head, Torso, Legged locomotion, fine-grained representation BibRef

Lyu, C.J.[Cheng-Jin], Heyer-Wollenberg, P.[Patrick], Platisa, L.[Ljiljana], Goossens, B.[Bart], Veelaert, P.[Peter], Philips, W.[Wilfried],
Clip-level Feature Aggregation: A Key Factor for Video-based Person Re-identification,
ACIVS20(179-191).
Springer DOI 2003
BibRef

Zheng, D.Y.[Ding-Yuan], Xiao, J.[Jimin], Huang, K.Z.[Kai-Zhu], Zhao, Y.[Yao],
Segmentation mask guided end-to-end person search,
SP:IC(86), 2020, pp. 115876.
Elsevier DOI 2006
Person search, Re-identification, Pedestrian detection, Segmentation masks, Background clutters BibRef

Lan, L.[Long], Wang, X.C.[Xin-Chao], Hua, G.[Gang], Huang, T.S.[Thomas S.], Tao, D.C.[Da-Cheng],
Semi-online Multi-people Tracking by Re-identification,
IJCV(128), No. 7, July 2020, pp. 1937-1955.
Springer DOI 2007
BibRef

Zhang, Z., Lan, C., Zeng, W., Jin, X., Chen, Z.,
Relation-Aware Global Attention for Person Re-Identification,
CVPR20(3183-3192)
IEEE DOI 2008
Semantics, Convolutional codes, Feature extraction, Benchmark testing, Aggregates, Stacking, Task analysis BibRef

Zhou, J.M.[Jie-Ming], Roy, S.K.[Soumava Kumar], Fang, P.F.[Peng-Fei], Harandi, M.[Mehrtash], Petersson, L.[Lars],
Cross-Correlated Attention Networks for Person Re-Identification,
IVC(100), 2020, pp. 103931.
Elsevier DOI 2008
Attention, Feature extraction, Cross correlation, Person Re-Identification, Surveillance BibRef


Li, M., Xu, H., Wang, J., Li, W., Sun, Y.,
Temporal Aggregation with Clip-level Attention for Video-based Person Re-identification,
WACV20(3365-3373)
IEEE DOI 2006
Feature extraction, Training, Task analysis, Measurement, Robustness, Computational modeling, Aggregates BibRef

Chen, Y., Zhu, X., Gong, S.,
Instance-Guided Context Rendering for Cross-Domain Person Re-Identification,
ICCV19(232-242)
IEEE DOI 2004
image matching, image recognition, neural nets, object recognition, rendering (computer graphics), supervised learning, Data models BibRef

Lu, R., Ma, H.,
Occluded Pedestrian Detection with Visible IoU and Box Sign Predictor,
ICIP19(1640-1644)
IEEE DOI 1910
Occluded pedestrian detection, visible ratio, box sign predictor, localization accuracy BibRef

Ghorbel, M.[Mahmoud], Ammar, S.[Sourour], Kessentini, Y.[Yousri], Jmaiel, M.[Mohamed],
Improving Person Re-identification by Background Subtraction Using Two-Stream Convolutional Networks,
ICIAR19(I:345-356).
Springer DOI 1909
BibRef

Zamprogno, M.[Marco], Passon, M.[Marco], Martinel, N.[Niki], Serra, G.[Giuseppe], Lancioni, G.[Giuseppe], Micheloni, C.[Christian], Tasso, C.[Carlo], Foresti, G.L.[Gian Luca],
Video-Based Convolutional Attention for Person Re-Identification,
CIAP19(I:3-14).
Springer DOI 1909
BibRef

Li, W.[Wenbo], Chen, Z.[Ze], Fu, Z.Y.[Zhen-Yong], Lu, H.T.[Hong-Tao],
Multilevel Collaborative Attention Network for Person Search,
ACCV18(I:467-482).
Springer DOI 1906
pedestrian detection and person re-identification simultaneously. BibRef

Ristani, E., Tomasi, C.,
Features for Multi-target Multi-camera Tracking and Re-identification,
CVPR18(6036-6046)
IEEE DOI 1812
Correlation, Cameras, Trajectory, Feature extraction, Training, Detectors, Benchmark testing BibRef

Babaee, M., Li, Z., Rigoll, G.,
Occlusion Handling in Tracking Multiple People Using RNN,
ICIP18(2715-2719)
IEEE DOI 1809
Target tracking, Training, Legged locomotion, Trajectory, Video sequences, Tracking, Motion, Occlusion, RNN, Deep learning BibRef

Huang, Z.X.[Zeng-Xi], Feng, Z.H.[Zhen-Hua], Yan, F.[Fei], Kittler, J.[Josef], Wu, X.J.[Xiao-Jun],
Robust Pedestrian Detection for Semi-automatic Construction of a Crowded Person Re-Identification Dataset,
AMDO18(63-72).
Springer DOI 1807
BibRef

Zhang, P.[Peng], Wu, Q.[Qiang], Xu, J.S.[Jing-Song], Zhang, J.[Jian],
Long-Term Person Re-identification Using True Motion from Videos,
WACV18(494-502)
IEEE DOI 1806
feature extraction, image coding, image matching, image motion analysis, image representation, image sequences, Videos BibRef

Wojke, N., Bewley, A.,
Deep Cosine Metric Learning for Person Re-identification,
WACV18(748-756)
IEEE DOI 1806
feature extraction, image classification, learning (artificial intelligence), query processing, vectors, Trajectory BibRef

Ustinova, E., Ganin, Y., Lempitsky, V.,
Multi-Region bilinear convolutional neural networks for person re-identification,
AVSS17(1-6)
IEEE DOI 1806
convolution, image classification, image matching, neural nets, bilinear pooling, bilinear-CNN architecture, Streaming media BibRef

Zhang, K.X.[Kai-Xuan], Xu, Y.[Yang], Sun, L.[Li], Qiu, S.[Song], Li, Q.L.[Qing-Li],
Person Re-id by Incorporating PCA Loss in CNN,
MMMod18(II:200-212).
Springer DOI 1802
BibRef

Peralta, B.[Billy], Caro, L.[Luis], Soto, A.[Alvaro],
Unsupervised Local Regressive Attributes for Pedestrian Re-identification,
CIARP17(517-524).
Springer DOI 1802
BibRef
Earlier: A1, A3, Only:
Multi-target Tracking with Sparse Group Features and Position Using Discrete-Continuous Optimization,
HIS14(680-694).
Springer DOI 1504
BibRef

Chahar, H.[Harendra], Nain, N.[Neeta],
A Study on Deep Convolutional Neural Network Based Approaches for Person Re-identification,
PReMI17(543-548).
Springer DOI 1711
BibRef

Xu, X., Ma, B.P.[Bing-Peng], Chang, H.[Hong], Chen, X.L.[Xi-Lin],
Siamese recurrent architecture for visual tracking,
ICIP17(1152-1156)
IEEE DOI 1803
Computer architecture, Recurrent neural networks, Target tracking, Training, Videos, Visualization, visual tracking BibRef

Deng, X.S.[Xue-Song], Ma, B.P.[Bing-Peng], Chang, H.[Hong], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
Deep Second-Order Siamese Network for Pedestrian Re-identification,
ACCV16(II: 321-337).
Springer DOI 1704
BibRef

Xu, B.[Bolei], Qiu, G.P.[Guo-Ping],
Unsupervised Person Re-identification via Graph-Structured Image Matching,
HIS16(III: 301-314).
Springer DOI 1704
BibRef

Huynh, X.P.[Xuan-Phung], Choi, I.H.[In-Ho], Kim, Y.G.[Yong-Guk],
Tracking a Human Fast and Reliably Against Occlusion and Human-Crossing,
PSIVT15(461-472).
Springer DOI 1602
BibRef

Zhou, Z.[Zhi], Wang, Y.[Yue], Teoh, E.K.[Eam Khwang],
Double layer salient parts based multi-people tracking,
ICIP15(3067-3071)
IEEE DOI 1512
Multi-people tracking BibRef

de Carvalho Prates, R.F.[Raphael Felipe], Schwartz, W.R.[William Robson],
CBRA: Color-based ranking aggregation for person re-identification,
ICIP15(1975-1979)
IEEE DOI 1512
color features BibRef

Si, J.L.[Jian-Lou], Zhang, H.G.[Hong-Gang], Li, C.G.[Chun-Guang],
Regularization in metric learning for person re-identification,
ICIP15(2309-2313)
IEEE DOI 1512
Metric Learning; Person Re-identification; Regularization BibRef

Huang, S.[Shuai], Gu, Y.[Yun], Yang, J.[Jie], Shi, P.F.[Peng-Fei],
Reranking of person re-identification by manifold-based approach,
ICIP15(4253-4257)
IEEE DOI 1512
manifold; re-identification; reranking BibRef

Tsai, M.C.[Ming-Chia], Wei, C.P.[Chia-Po], Wang, Y.C.A.F.[Yu-Chi-Ang Frank],
Graph regularized low-rank matrix recovery for robust person re-identification,
ICIP15(4654-4658)
IEEE DOI 1512
Graph Regularization; Low-Rank Matrix Recovery; Person Re-Identification BibRef

Fagot-Bouquet, L.[Loďc], Audigier, R.[Romaric], Dhome, Y.[Yoann], Lerasle, F.[Frédéric],
Improving Multi-frame Data Association with Sparse Representations for Robust Near-online Multi-object Tracking,
ECCV16(VIII: 774-790).
Springer DOI 1611
BibRef
And:
Online multi-person tracking based on global sparse collaborative representations,
ICIP15(2414-2418)
IEEE DOI 1512
BibRef
Earlier:
Collaboration and spatialization for an efficient multi-person tracking via sparse representations,
AVSS15(1-6)
IEEE DOI 1511
Online tracking. computer vision BibRef

Ristani, E.[Ergys], Tomasi, C.[Carlo],
Tracking Multiple People Online and in Real Time,
ACCV14(V: 444-459).
Springer DOI 1504
BibRef

Mansouri, N., Ben Jemaa, Y., Motamed, C., Pinti, A., Watelain, E.,
A new strategy based on spatiogram similarity association for multi-pedestrian tracking,
IPTA14(1-6)
IEEE DOI 1503
image sequences BibRef

Chen, J.H.[Jia-Hui], Sheng, H.[Hao], Zhang, Y.[Yang], Xiong, Z.[Zhang],
Enhancing Detection Model for Multiple Hypothesis Tracking,
PETS17(2143-2152)
IEEE DOI 1709
Analytical models, Cameras, Correlation, Detectors, Target tracking, Trajectory BibRef

Sheng, H.[Hao], Liu, S.[Shukai], Ji, H.S.[Heng-Shan], Chen, J.H.[Jia-Hui], Xiong, Z.[Zhang],
A Pedestrian-Pedestrian and Pedestrian-Vehicle Interaction Motion Model for Pedestrians Tracking,
ISVC14(I: 270-280).
Springer DOI 1501
BibRef

Pham, V.Q.[Viet-Quoc], Kozakaya, T.[Tatsuo], Okada, R.[Ryuzo],
DIET: Dynamic Integration of Extended Tracklets for Tracking Multiple Persons,
ICPR14(1206-1211)
IEEE DOI 1412
Cities and towns BibRef

Yan, X.[Xu], Cheriyadat, A.[Anil], Shah, S.K.[Shishir K.],
Hierarchical Group Structures in Multi-person Tracking,
ICPR14(2221-2226)
IEEE DOI 1412
Dynamics BibRef

Gudys, A.[Adam], Rosner, J.[Jakub], Segen, J.[Jakub], Wojciechowski, K.[Konrad], Kulbacki, M.[Marek],
Tracking People in Video Sequences by Clustering Feature Motion Paths,
ICCVG14(236-245).
Springer DOI 1410
BibRef

Henschel, R.[Roberto], Leal-Taixé, L.[Laura], Rosenhahn, B.[Bodo],
Solving Multiple People Tracking in a Minimum Cost Arborescence,
MTT15(71-72)
IEEE DOI 1503
BibRef
Earlier:
Efficient Multiple People Tracking Using Minimum Cost Arborescences,
GCPR14(265-276).
Springer DOI 1411
BibRef

Xiang, Y., Alahi, A.[Alexandre], Savarese, S.[Silvio],
Learning to Track: Online Multi-object Tracking by Decision Making,
ICCV15(4705-4713)
IEEE DOI 1602
Decision making BibRef

Leal-Taixe, L.[Laura], Fenzi, M.[Michele], Kuznetsova, A.[Alina], Rosenhahn, B.[Bodo], Savarese, S.[Silvio],
Learning an Image-Based Motion Context for Multiple People Tracking,
CVPR14(3542-3549)
IEEE DOI 1409
image-based motion context BibRef

Wang, B.[Bing], Wang, G.[Gang], Chan, K.L.[Kap Luk], Wang, L.[Li],
Tracklet Association in Detect-Then-Track Paradigm for Long-Term Multi-person Tracking,
LTDT14(716-717)
IEEE DOI 1409
BibRef

Zhang, J.M.[Jian-Ming], lo Presti, L.[Liliana], Sclaroff, S.[Stan],
Online Multi-person Tracking by Tracker Hierarchy,
AVSS12(379-385).
IEEE DOI 1211
BibRef

Nie, W.Z.[Wei-Zhi], Liu, A.A.[An-An], Su, Y.T.[Yu-Ting],
Multiple Person Tracking by Spatiotemporal Tracklet Association,
AVSS12(481-486).
IEEE DOI 1211
BibRef

Jiang, X.Y.[Xiao-Yan], Rodner, E.[Erik], Denzler, J.[Joachim],
Multi-person Tracking-by-Detection Based on Calibrated Multi-camera Systems,
ICCVG12(743-751).
Springer DOI 1210
BibRef

Piatkowska, E.[Ewa], Kogler, J., Belbachir, A.N.[Ahmed Nabil], Gelautz, M.[Margrit],
Improved Cooperative Stereo Matching for Dynamic Vision Sensors with Ground Truth Evaluation,
ECVW17(370-377)
IEEE DOI 1709
BibRef
Earlier: A1, A3, A4, Only:
Asynchronous Stereo Vision for Event-Driven Dynamic Stereo Sensor Using an Adaptive Cooperative Approach,
CDC4CV13(45-50)
IEEE DOI 1403
Biosensors, Cameras, Computer vision, Heuristic algorithms, Voltage control. BibRef

Piatkowska, E.[Ewa], Belbachir, A.N.[Ahmed Nabil], Schraml, S.[Stephan], Gelautz, M.[Margrit],
Spatiotemporal multiple persons tracking using Dynamic Vision Sensor,
ECVW12(35-40).
IEEE DOI 1207
BibRef

Heili, A.[Alexandre], Odobez, J.M.[Jean-Marc],
Parameter estimation and contextual adaptation for a multi-object tracking CRF model,
PETS13(14-21)
IEEE DOI 1411
object detection BibRef

Heili, A.[Alexandre], Chen, C.[Cheng], Odobez, J.M.[Jean-Marc],
Detection-based multi-human tracking using a CRF model,
VS11(1673-1680).
IEEE DOI 1201
BibRef

Luo, X.H.[Xing-Han], Tan, R.T.[Robby T.], Veltkamp, R.C.[Remco C.],
Multi-person tracking based on vertical reference lines and dynamic visibility analysis,
ICIP11(1877-1880).
IEEE DOI 1201
BibRef

Thaler, M.[Marcus], Bailer, W.[Werner],
Real-Time Person Detection and Tracking in Panoramic Video,
CVSports13(1027-1032)
IEEE DOI 1309
broadcast; detection; panoramic; sports; tracking BibRef

Thaler, M.[Marcus], Kaiser, R.[Rene], Bailer, W.[Werner], Kriechbaum, A.[Andreas],
Tracking Persons in Ultra-HD Panoramic Video,
MMMod12(633-635).
Springer DOI 1201
BibRef

Yeh, H.H.[Hsin-Ho], Chen, J.Y.[Jiun-Yu], Huang, C.R.[Chun-Rong], Chen, C.S.[Chu-Song],
An adaptive approach for overlapping people tracking based on foreground silhouettes,
ICIP10(3489-3492).
IEEE DOI 1009
BibRef

Galoogahi, H.K.,
Tracking Groups of People in Presence of Occlusion,
PSIVT10(438-443).
IEEE DOI 1011
BibRef

Zen, G.[Gloria], Lanz, O.[Oswald], Messelodi, S.[Stefano], Ricci, E.[Elisa],
Tracking Multiple People with Illumination Maps,
ICPR10(3484-3487).
IEEE DOI 1008
BibRef

Bütepage, J., Black, M.J., Kragic, D.[Danica], Kjellström, H.[Hedvig],
Deep Representation Learning for Human Motion Prediction and Classification,
CVPR17(1591-1599)
IEEE DOI 1711
Computational modeling, Correlation, Decoding, Encoding, Feature extraction, Hidden, Markov, models BibRef

Kjellstrom, H.[Hedvig], Kragic, D.[Danica], Black, M.J.[Michael J.],
Tracking people interacting with objects,
CVPR10(747-754).
IEEE DOI 1006
BibRef

Breitenstein, M.D.[Michael D.], Reichlin, F.[Fabian], Leibe, B.[Bastian], Koller-Meier, E.[Esther], Van Gool, L.J.[Luc J.],
Robust tracking-by-detection using a detector confidence particle filter,
ICCV09(1515-1522).
IEEE DOI 0909
multi-person tracking. Particle filter framework. BibRef

Ishiguro, K.[Katsuhiko], Yamada, T.[Takeshi], Ueda, N.[Naonori],
Simultaneous clustering and tracking unknown number of objects,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Apewokin, S., Valentine, B., Bales, M.R.[M. Ryan], Wills, L.M.[Linda M.], Wills, D.S.[D. Scott],
Tracking multiple pedestrians in real-time using kinematics,
EmbedCV08(1-6).
IEEE DOI 0806
BibRef

Boufama, B., Ali, M.A.,
Tracking Multiple People in the Context of Video Surveillance,
ICIAR07(581-592).
Springer DOI 0708
BibRef

Feldmann, T.[Tobias], Scheuermann, B.[Björn], Rosenhahn, B.[Bodo], Wörner, A.[Annika],
N-View Human Silhouette Segmentation in Cluttered, Partially Changing Environments,
DAGM10(363-372).
Springer DOI 1009
BibRef

Rosenhahn, B.[Bodo], Klette, R.[Reinhard], Sommer, G.[Gerald],
Silhouette Based Human Motion Estimation,
DAGM04(294-301).
Springer DOI 0505
BibRef

Girondel, V., Caplier, A., Bonnaud, L.,
Real time tracking of multiple persons by Kalman filtering and face pursuit for multimedia applications,
Southwest04(201-205).
IEEE DOI 0411
BibRef

Mori, T.[Taketoshi], Matsumoto, T.[Takashi], Shimosaka, M.[Masamichi], Noguchi, H.[Hiroshi], Sato, T.[Tomomasa],
Multiple Persons Tracking with Data Fusion of Multiple Cameras and Sensing Floor Using Particle Filters,
M2SFA208(xx-yy). 0810
BibRef

Harada, T.[Tatsuya], Sato, T.[Tomomasa], Mori, T.[Taketoshi],
Human Motion Tracking System Based on Skeleton and Surface Integration Model Using Pressure Sensors Distribtuion Bed,
HUMO00(99-106).
IEEE Top Reference. 0010
BibRef

Roh, H., Kang, S., Lee, S.W.,
Multiple People Tracking Using Appearance Model Based on Temporal Color,
ICPR00(Vol IV: 643-646).
IEEE DOI 0009
BibRef

Bernier, O.J.[Olivier J.], Collobert, M., Feraud, R., Lemaire, V., Viallet, J.E., Collobert, D.,
MULTRAK: a system for automatic multiperson localization and tracking in real-time,
ICIP98(I: 136-140).
IEEE DOI 9810
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Tracking People, Re-Identification Issues, Occlusions .


Last update:Sep 21, 2020 at 13:40:48