16.7.4.4.2 Tracking Several People, Occlusions

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

Lejbølle, 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

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

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

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.[Low], Audigier, R.[Romaric], Dhome, Y.[Yoann], Lerasle, F.[Frederic],
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:Mar 29, 2020 at 12:14:19