16.7.4.4.2 Tracking Several People, Occlusions

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

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

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.[Loïc], 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