17.1.3.4 Tracking People, Human Tracking, Pedestrian Tracking

Chapter Contents (Back)
Tracking. Human Motion. Human Tracking. Pedestrian Tracking.
See also Pedestrian Trajectory Analysis, Pedestrian Tracking.
See also Human Detection, People Detection, Pedestrians, Locating.
See also Tracking People with Stereo, or Depth.
See also Tracking People, Re-Identification Issues, Learning.

Lai, J.Z.C.[Jim Z.C],
Tracking Multiple Features Using Relaxation,
PR(26), No. 12, December 1993, pp. 1827-1837.
Elsevier DOI Human motion tracking. BibRef 9312

Sethi, I.K.[Ishwar K.],
Tracking Multiple Features Using Relaxation: Comments,
PR(27), No. 6, June 1994, pp. 865.
Elsevier DOI BibRef 9406

Ledley, R.S.,
Tracking Multiple Features Using Relaxation: Reply,
PR(27), No. 6, June 1994, pp. 865.
Elsevier DOI BibRef 9406

Ye, Y.M.[Yi-Ming], Tsotsos, J.K.[John K.], Harley, E.[Eric], Bennet, K.[Karen],
Tracking a Person with Pre-Recorded Image Database by a Pan, Tilt, and Zoom Camera,
MVA(12), No. 1, 2000, pp. 32-43.
Springer DOI 0008
BibRef
Earlier: A1, A2, A4, A3: VS98(Monitoring and Surveillance of People). BibRef

Crabtree, R.N.[Ralph N.], Moed, M.C.[Michael C.], Khosravi, M.[Mehdi],
System and method for tracking movement of objects in a scene,
US_Patent6,263,088, Jul 17, 2001
WWW Link. BibRef 0107

Rehg, J.M.[James Matthew], Morris, D.D.[Daniel D.],
Method for figure tracking using 2-D registration,
US_Patent6,240,198, May 29, 2001
WWW Link. BibRef 0105
And: A2, A1:
Singularity Analysis for Articulated Object Tracking,
CVPR98(289-296).
IEEE DOI BibRef

Rehg, J.M.[James Matthew], Morris, D.D.[Daniel D.],
Method and system for compressing a sequence of images including a moving figure,
US_Patent6,256,418, Jul 3, 2001
WWW Link. BibRef 0107
And:
Method for tracking the motion of a 3-D figure,
US_Patent6,269,172, Jul 31, 2001
WWW Link. BibRef

Fathi, A.[Alireza], Balcan, M.F.[Maria Florina], Ren, X.F.[Xiao-Feng], Rehg, J.M.[James M.],
Combining Self Training and Active Learning for Video Segmentation,
BMVC11(xx-yy).
HTML Version. 1110
Not just people. But that kind of moving object. BibRef

Jang, D.S.[Dae-Sik], Jang, S.W.[Seok-Woo], Choi, H.I.[Hyung-Il],
2D human body tracking with Structural Kalman filter,
PR(35), No. 10, October 2002, pp. 2041-2049.
Elsevier DOI 0206
BibRef

Loveland, R.C.[Rohan Christopher],
Automated video person tracking system,
US_Patent6,437,819, Aug 20, 2002
WWW Link. BibRef 0208

Kapoor, A.[Ashish], Grauman, K.[Kristen], Urtasun, R.[Raquel], Darrell, T.J.[Trevor J.],
Gaussian Processes for Object Categorization,
IJCV(88), No. 2, June 2010, pp. xx-yy.
Springer DOI 1003
BibRef
Earlier:
Active Learning with Gaussian Processes for Object Categorization,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Jain, P.[Prateek], Kapoor, A.[Ashish],
Active learning for large multi-class problems,
CVPR09(762-769).
IEEE DOI 0906
BibRef

Chen, Z.[Zhuo], Wang, L.[Lu], Yung, N.H.C.[Nelson H.C.],
Adaptive human motion analysis and prediction,
PR(44), No. 12, December 2011, pp. 2902-2914.
Elsevier DOI 1107
Motion pattern; Pattern clustering; Pattern classification; Prediction BibRef

Vijayanarasimhan, S.[Sudheendra], Grauman, K.[Kristen],
Cost-Sensitive Active Visual Category Learning,
IJCV(91), No. 1, January 2011, pp. 24-44.
WWW Link. 1101
o
See also Fast Similarity Search for Learned Metrics. BibRef

Vijayanarasimhan, S.[Sudheendra], Grauman, K.[Kristen],
Efficient region search for object detection,
CVPR11(1401-1408).
IEEE DOI 1106
BibRef

Vijayanarasimhan, S.[Sudheendra], Grauman, K.[Kristen],
Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds,
IJCV(108), No. 1-2, May 2014, pp. 97-114.
WWW Link. 1405
BibRef
Earlier: CVPR11(1449-1456).
IEEE DOI 1106
BibRef
Earlier:
What's it going to cost you?: Predicting effort vs. informativeness for multi-label image annotations,
CVPR09(2262-2269).
IEEE DOI 0906
BibRef
Earlier:
Keywords to visual categories: Multiple-instance learning for weakly supervised object categorization,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Fan, L.X.[Li-Xin], Sung, K.K.[Kah-Kay], Ng, T.K.[Teck-Khim],
Pedestrian registration in static images with unconstrained background,
PR(36), No. 4, April 2003, pp. 1019-1029.
Elsevier DOI 0304
BibRef

Metoyer, R.A.[Ronald A.], Hodgins, J.K.[Jessica K.],
Reactive pedestrian path following from examples,
VC(20), No. 10, December 2004, pp. 635-649.
Springer DOI 0412
BibRef

Matsuo, H.[Hideaki], Imagawa, K.[Kazuyuki], Takata, Y.J.[Yu-Ji],
Human tracking device, human tracking method and recording medium recording program thereof,
US_Patent6,704,433, Mar 9, 2004
WWW Link. BibRef 0403

Fujie, H.[Hidekatsu],
Monitoring system and method,
US_Patent7,158,038, Jan 2, 2007
WWW Link. Human motion detection BibRef 0701

Denman, S.[Simon], Chandran, V.[Vinod], Sridharan, S.[Sridha],
An adaptive optical flow technique for person tracking systems,
PRL(28), No. 10, 15 July 2007, pp. 1232-1239.
Elsevier DOI 0706
Person tracking; Optical flow; Motion detection BibRef

Hua, C.S.[Chun-Sheng], Wu, H.Y.[Hai-Yuan], Chen, Q.[Qian], Wada, T.[Toshikazu],
Object Tracking with Target and Background Samples,
IEICE(E90-D), No. 4, April 2007, pp. 766-774.
DOI Link 0704
BibRef
Earlier:
A Pixel-wise Object Tracking Algorithm with Target and Background Sample,
ICPR06(I: 739-742).
IEEE DOI 0609
BibRef
And:
A General Framework For Tracking People,
FGR06(511-516).
IEEE DOI 0604
BibRef

Hua, C.S.[Chun-Sheng], Chen, Q.[Qian], Wu, H.Y.[Hai-Yuan], Wada, T.[Toshikazu],
A Noise-Insensitive Object Tracking Algorithm,
ACCV07(I: 565-575).
Springer DOI 0711
BibRef

Junejo, I.N.[Imran N.], Foroosh, H.[Hassan],
Euclidean path modeling for video surveillance,
IVC(26), No. 4, April 2008, pp. 512-528.
Elsevier DOI 0711
BibRef
Earlier:
Trajectory Rectification and Path Modeling for Video Surveillance,
ICCV07(1-7).
IEEE DOI 0710
BibRef
Earlier:
Using Calibrated Camera for Euclidean Path Modeling,
ICIP07(III: 205-208).
IEEE DOI 0709
BibRef
And:
Euclidean Path Modeling from Ground and Aerial Views,
VS07(1-6).
IEEE DOI 0706
Path modeling; Pedestrian surveillance; Metric rectification; Camera auto-calibration; Trajectory clustering; Route detection Path modeling in a single camera for activity monitoring in a multi-camera video surveillance system. BibRef

Junejo, I.N.[Imran N.], Foroosh, H.[Hassan],
Estimating Geo-temporal Location of Stationary Cameras Using Shadow Trajectories,
ECCV08(I: 318-331).
Springer DOI 0810

See also Simple Shadow Based Method for Camera Calibration, A. BibRef

Junejo, I.N.[Irnran N.], Cao, X.C.[Xiao-Chun], Foroosh, H.[Hassan],
Geometry of a Non-Overlapping Multi-Camera Network,
AVSBS06(43-43).
IEEE DOI 0611
BibRef

Junejo, I.N.[Imran N.],
Using dynamic Bayesian network for scene modeling and anomaly detection,
SIViP(4), No. 1, March 2010, pp. xx-yy.
Springer DOI 1003
BibRef

Karlsson, S.[Stefan], Taj, M.[Murtaza], Cavallaro, A.[Andrea],
Detection and Tracking of Humans and Faces,
JIVP(2008), No. 2008, pp. xx-yy.
DOI Link 0804
BibRef

Snidaro, L.[Lauro], Foresti, G.L.[Gian Luca], Chittaro, L.[Luca],
Tracking Human Motion From Monocular Sequences,
IJIG(8), No. 3, July 2008, pp. 455-471. 0807
BibRef

Snidaro, L.[Lauro], Visentini, I.[Ingrid], Foresti, G.L.[Gian Luca],
Multi-sensor Multi-cue Fusion for Object Detection in Video Surveillance,
AVSBS09(364-369).
IEEE DOI 0909
BibRef

Snidaro, L.[Lauro], Visentini, I.[Ingrid], Foresti, G.L.[Gian Luca],
Dynamic Models for People Detection and Tracking,
AVSBS08(29-35).
IEEE DOI 0809
BibRef
And: A2, A1, A3:
Dynamic ensemble for target tracking,
VS08(xx-yy). 0810

See also Commentary Paper on Dynamic Models for People Detection and Tracking. BibRef

Tao, J.[Ji], Tan, Y.P.[Yap-Peng], Lu, W.M.[Wen-Miao],
Robust Color Object Tracking With Application To People Monitoring,
IJIG(7), No. 2, April 2007, pp. 227-254. 0704
BibRef

Shen, S.H.[Shu-Han], Tong, M.L.[Ming-Lei], Deng, H.L.[Hao-Long], Liu, Y.C.[Yun-Cai], Wu, X.J.[Xiao-Jun], Wakabayashi, K.[Kaoru], Koike, H.[Hideki],
Model based human motion tracking using probability evolutionary algorithm,
PRL(29), No. 13, 1 October 2008, pp. 1877-1886.
Elsevier DOI 0804
Tracking; Human tracking; Probability evolutionary algorithm BibRef

Xiang, S.M.[Shi-Ming], Nie, F.P.[Fei-Ping], Song, Y.Q.[Yang-Qiu], Zhang, C.S.[Chang-Shui],
Contour graph based human tracking and action sequence recognition,
PR(41), No. 12, December 2008, pp. 3653-3664.
Elsevier DOI 0810
Contour tracking; Sequence recognition; Sequence Monte Carlo estimation; Contour graph; Diving action BibRef

Leibe, B.[Bastian], Schindler, K.[Konrad], Cornelis, N.[Nico], Van Gool, L.J.[Luc J.],
Coupled Object Detection and Tracking from Static Cameras and Moving Vehicles,
PAMI(30), No. 10, October 2008, pp. 1683-1698.
IEEE DOI 0810
BibRef
Earlier: A1, A2, A4, Only:
Coupled Detection and Trajectory Estimation for Multi-Object Tracking,
ICCV07(1-8).
IEEE DOI Award, CVPR. 0710
At each step search for global set of trajectories that best fit the data. BibRef

Sudowe, P.[Patrick], Leibe, B.[Bastian],
Efficient Use of Geometric Constraints for Sliding-Window Object Detection in Video,
CVS11(11-20).
Springer DOI 1109
BibRef

Izadi, M.[Mohammad], Safabakhsh, R.[Reza],
An improved time-adaptive self-organizing map for high-speed shape modeling,
PR(42), No. 7, July 2009, pp. 1361-1370.
Elsevier DOI 0903
Active contour model; Time-adaptive self-organizing map; TASOM; Adaptive speed parameter; Boundary curvature; Person tracking BibRef

Liu, C.[Chang], Wang, G.J.[Gui-Jin], Jiang, F.[Fan], Lin, X.G.[Xing-Gang],
Online HOG Method in Pedestrian Tracking,
IEICE(E93-D), No. 5, May 2010, pp. 1321-1324.
WWW Link. 1006
BibRef

Jiang, F.[Fan], Wang, G.J.[Gui-Jin], Liu, C.[Chang], Lin, X.G.[Xing-Gang], Wu, W.G.[Wei-Guo],
Robust Object Tracking via Combining Observation Models,
IEICE(E93-D), No. 3, March 2010, pp. 662-665.
WWW Link. 1003
BibRef

Han, Z.J.[Zhen-Jun], Ye, Q.X.[Qi-Xiang], Jiao, J.B.[Jian-Bin],
Combined feature evaluation for adaptive visual object tracking,
CVIU(115), No. 1, January 2011, pp. 69-80.
Elsevier DOI 1011
BibRef
Earlier:
Online feature evaluation for object tracking using Kalman Filter,
ICPR08(1-4).
IEEE DOI 0812
Object tracking; Color histogram; Gradient orientation histogram; Kalman filter; Particle filter BibRef

Han, Z.J.[Zhen-Jun], Jiao, J.B.[Jian-Bin], Zhang, B.C.[Bao-Chang], Ye, Q.X.[Qi-Xiang], Liu, J.Z.[Jian-Zhuang],
Visual object tracking via sample-based Adaptive Sparse Representation (AdaSR),
PR(44), No. 9, September 2011, pp. 2170-2183.
Elsevier DOI 1106
Object tracking; Sample-Based Representation; Adaptive sparse representation BibRef

Han, Z.J.[Zhen-Jun], Ye, Q.X.[Qi-Xiang], Jiao, J.B.[Jian-Bin],
Robust Visual Object Tracking via Sparse Representation and Reconstruction,
CAIP13(II:282-289).
Springer DOI 1311
BibRef

Zhang, B.C.[Bao-Chang], Zhang, S.P.[Sheng-Ping], Liu, J.Z.[Jian-Zhuang],
Sparse regression analysis for object recognition,
ICIP11(2381-2384).
IEEE DOI 1201
BibRef

Han, Z.J.[Zhen-Jun], Jiao, J.B.[Jian-Bin], Ye, Q.X.[Qi-Xiang],
A fast object tracking approach based on sparse representation,
ICIP11(1865-1868).
IEEE DOI 1201
BibRef

Li, L.[Li], Han, Z.J.[Zhen-Jun], Ye, Q.X.[Qi-Xiang], Jiao, J.B.[Jian-Bin],
Visual Object Tracking via One-Class SVM,
VS10(216-225).
Springer DOI 1109
BibRef

Ye, Q.X.[Qi-Xiang], Jiao, J.B.[Jian-Bin], Zhang, B.C.[Bao-Chang],
Fast pedestrian detection with multi-scale orientation features and two-stage classifiers,
ICIP10(881-884).
IEEE DOI 1009
BibRef

Xu, R.[Ran], Jiao, J.B.[Jian-Bin], Zhang, B.C.[Bao-Chang], Ye, Q.X.[Qi-Xiang],
Pedestrian detection in images via cascaded L1-norm minimization learning method,
PR(45), No. 7, July 2012, pp. 2573-2583.
Elsevier DOI 1203
BibRef
Earlier: A1, A3, A4, A2:
Cascaded L1-norm Minimization Learning (CLML) classifier for human detection,
CVPR10(89-96).
IEEE DOI 1006
Pedestrian detection; L1-norm minimization; Feature selection; Cascaded classifier BibRef

Xu, R.[Ran], Jiao, J.B.[Jian-Bin], Ye, Q.X.[Qi-Xiang],
Nonlinear L1-norm minimization learning for human detection,
ICIP11(3573-3576).
IEEE DOI 1201
BibRef

Ye, Q.X.[Qi-Xiang], Jiao, J.B.[Jian-Bin], Yu, H.[Hua],
Multi-posture Human Detection in Video Frames by Motion Contour Matching,
ACCV07(I: 896-904).
Springer DOI 0711
BibRef

Assheton, P., Hunter, A.,
A shape-based voting algorithm for pedestrian detection and tracking,
PR(44), No. 5, May 2011, pp. 1106-1120.
Elsevier DOI 1101
Scene analysis; Shape tracking; Hough transform; Video analysis BibRef

Varcheie, P.D.Z.[Parisa Darvish Zadeh], Bilodeau, G.A.[Guillaume-Alexandre],
People tracking using a network-based PTZ camera,
MVA(22), No. 4, July 2011, pp. 671-690.
WWW Link. 1107
BibRef
Earlier:
Fuzzy Feature-Based Upper Body Tracking with IP PTZ Camera Control,
CIARP09(809-816).
Springer DOI 0911
BibRef
And:
Human Tracking by IP PTZ Camera Control in the Context of Video Surveillance,
ICIAR09(657-667).
Springer DOI 0907
BibRef

Bouachir, W.[Wassim], Bilodeau, G.A.[Guillaume-Alexandre],
Collaborative part-based tracking using salient local predictors,
CVIU(137), No. 1, 2015, pp. 88-101.
Elsevier DOI 1506
BibRef
Earlier:
Part-Based Tracking via Salient Collaborating Features,
WACV15(78-85)
IEEE DOI 1503
Computational modeling. Part-based tracking BibRef

Bourezak, R.[Rafik], Bilodeau, G.A.[Guillaume-Alexandre],
Iterative Division and Correlograms for Detection and Tracking of Moving Objects,
IWICPAS06(46-55).
Springer DOI 0608
BibRef
And:
Object detection and tracking using iterative division and correlograms,
CRV06(38-38).
IEEE DOI 0607
BibRef

Wang, M., Qiao, H., Zhang, B.,
A New Algorithm for Robust Pedestrian Tracking Based on Manifold Learning and Feature Selection,
ITS(12), No. 4, December 2011, pp. 1195-1208.
IEEE DOI 1112
BibRef

Liu, C.M.[Chun-Mei], Hu, C.B.[Chang-Bo], Aggarwal, J.K.,
Eigenshape kernel based mean shift for human tracking,
VS11(1809-1816).
IEEE DOI 1201
BibRef

Motai, Y.[Yuichi], Jha, S.K.[Sumit Kumar], Kruse, D.[Daniel],
Human tracking from a mobile agent: Optical flow and Kalman filter arbitration,
SP:IC(27), No. 1, January 2012, pp. 83-95.
Elsevier DOI 1201
Human tracking; Kalman filter; Mobile robot; Optical flow BibRef

Wang, J.T.[Jian-Tao], Chen, D.B.[De-Bao], Chen, H.Y.[Hai-Yan], Yang, J.Y.[Jing-Yu],
On pedestrian detection and tracking in infrared videos,
PRL(33), No. 6, 15 April 2012, pp. 775-785.
Elsevier DOI 1203
Infrared pedestrian detection; Infrared pedestrian tracking; Multi-cue fusion; Particle filter BibRef

Ma, G., Müller, D.[Dennis], Park, S.B.[Su-Birm], Müller-Schneiders, S.[Stefan], Kummert, A.[Anton],
Pedestrian detection using a single monochrome camera,
IET-ITS(3), No. 1, 2009, pp. 42-56.
DOI Link 1204
BibRef

Meuter, M.[Mirko], Müller, D.[Dennis], Müller-Schneiders, S.[Stefan], Iurgel, U.[Uri], Park, S.B.[Su-Birm], Kummert, A.[Anton],
Pedestrian Tracking from a Moving Host Using Corner Points,
ISVC07(II: 367-376).
Springer DOI 0711
BibRef

Khanloo, B.Y.S.[Bahman Yari Saeed], Stefanus, F.[Ferdinand], Ranjbar, M.[Mani], Li, Z.N.[Ze-Nian], Saunier, N.[Nicolas], Sayed, T.[Tarek], Mori, G.[Greg],
A large margin framework for single camera offline tracking with hybrid cues,
CVIU(116), No. 6, June 2012, pp. 676-689.
Elsevier DOI 1204
BibRef
Earlier:
Max-Margin Offline Pedestrian Tracking with Multiple Cues,
CRV10(347-353).
IEEE DOI 1005
Tracking; Trajectory optimization; Structured prediction; Conditional random fields; Discriminative learning BibRef

García-Martín, Á.[Álvaro], Martínez, J.M.[José M.],
On collaborative people detection and tracking in complex scenarios,
IVC(30), No. 4-5, May 2012, pp. 345-354.
Elsevier DOI 1206
People detection; People tracking; Collaborative system; Video surveillance BibRef

García-Martín, Á.[Álvaro], Martínez, J.M.[José M.],
Post-processing approaches for improving people detection performance,
CVIU(133), No. 1, 2015, pp. 76-89.
Elsevier DOI 1502
People detection
See also Pedestrian Detection: An Evaluation of the State of the Art. BibRef

Metternich, M.J.[Michael J.], Worring, M.[Marcel],
Track based relevance feedback for tracing persons in surveillance videos,
CVIU(117), No. 3, March 2013, pp. 229-237.
Elsevier DOI 1302
Surveillance; Event reconstruction; Person tracing; Relevance feedback BibRef

Garcia, J., Gardel, A., Bravo, I., Lazaro, J.L., Martinez, M.,
Tracking People Motion Based on Extended Condensation Algorithm,
SMCS(43), No. 3, May 2013, pp. 606-618.
IEEE DOI 1305
BibRef

di Lascio, R.[Rosario], Foggia, P.[Pasquale], Percannella, G.[Gennaro], Saggese, A.[Alessia], Vento, M.[Mario],
A real time algorithm for people tracking using contextual reasoning,
CVIU(117), No. 8, August 2013, pp. 892-908.
Elsevier DOI 1306
BibRef
Earlier: A2, A3, A4, A5, Only:
Real-time tracking of single people and groups simultaneously by contextual graph-based reasoning dealing complex occlusions,
PETS13(29-36)
IEEE DOI 1411
finite state machines Video surveillance; Real-time object tracking; Finite State Automata BibRef

Shabani, A.H.[Amir-Hossein], Zelek, J.S.[John S.], Clausi, D.A.[David A.],
Multiple scale-specific representations for improved human action recognition,
PRL(34), No. 15, 2013, pp. 1771-1779.
Elsevier DOI 1309
BibRef
Earlier: A1, A3, A2:
Evaluation of Local Spatio-temporal Salient Feature Detectors for Human Action Recognition,
CRV12(468-475).
IEEE DOI 1207
BibRef
And: A1, A3, A2:
Improved Spatio-temporal Salient Feature Detection for Action Recognition,
BMVC11(xx-yy).
HTML Version. 1110
BibRef
Earlier: A1, A2, A3:
Human Action Recognition Using Salient Opponent-Based Motion Features,
CRV10(362-369).
IEEE DOI 1005
BibRef
Earlier: A1, A3, A2:
Towards a Robust Spatio-Temporal Interest Point Detection for Human Action Recognition,
CRV09(237-243).
IEEE DOI 0905
Human action recognition BibRef

El Nabbout, N.M.[Nathalie M.], Zelek, J.S.[John S.], Clausi, D.A.[David A.],
Automatically Detecting and Tracking People Walking through a Transparent Door with Vision,
CRV08(171-178).
IEEE DOI 0805
BibRef

Ghaeminia, M.H.[Mohammad Hossein], Badiezadeh, A., Shokouhi, S.B.[Shahryar Baradaran],
An Efficient Energy Model for Human Gait Recognition,
DICTA16(1-6)
IEEE DOI 1701
Computational modeling BibRef

Ghaeminia, M.H.[Mohammad Hossein], Shabani, A.H.[Amir Hossein], Shokouhi, S.B.[Shahryar Baradaran],
Adaptive Motion Model for Human Tracking Using Particle Filter,
ICPR10(2073-2076).
IEEE DOI 1008
BibRef
Earlier: A2, A1, A3:
Human Tracking Using Spatialized Multi-level Histogram and Mean Shift,
CRV10(151-158).
IEEE DOI 1005
BibRef

Zuriarrain, I.[Iker], Mekonnen, A.A.[Alhayat Ali], Lerasle, F.[Frédéric], Arana, N.[Nestor],
Tracking-by-detection of multiple persons by a resample-move particle filter,
MVA(24), No. 8, November 2013, pp. 1751-1765.
Springer DOI 1310

See also Cooperative passers-by tracking with a mobile robot and external cameras. BibRef

Moussy, E., Mekonnen, A.A., Marion, G., Lerasle, F.,
A comparative view on exemplar 'tracking-by-detection' approaches,
AVSS15(1-6)
IEEE DOI 1511
Monte Carlo methods BibRef

Führ, G.[Gustavo], Jung, C.R.[Cláudio Rosito],
Combining patch matching and detection for robust pedestrian tracking in monocular calibrated cameras,
PRL(39), No. 1, 2014, pp. 11-20.
Elsevier DOI 1402
Patch-based tracking BibRef

Yuan, Y.[Yuan], Fang, J.W.[Jian-Wu], Wang, Q.[Qi],
Robust Superpixel Tracking via Depth Fusion,
CirSysVideo(24), No. 1, January 2014, pp. 15-26.
IEEE DOI 1402
graph theory BibRef

Keller, C.G., Gavrila, D.M.,
Will the Pedestrian Cross? A Study on Pedestrian Path Prediction,
ITS(15), No. 2, April 2014, pp. 494-506.
IEEE DOI 1404
Data models BibRef

Schneider, N.[Nicolas], Gavrila, D.M.[Dariu M.],
Pedestrian Path Prediction with Recursive Bayesian Filters: A Comparative Study,
GCPR13(174-183).
Springer DOI 1311
BibRef

Heili, A.[Alexander], Lopez-Mendez, A., Odobez, J.M.[Jean-Marc],
Exploiting Long-Term Connectivity and Visual Motion in CRF-Based Multi-Person Tracking,
IP(23), No. 7, July 2014, pp. 3040-3056.
IEEE DOI 1407
Feature extraction BibRef

Le, N.[Nam], Heili, A.[Alexander], Odobez, J.M.[Jean-Marc],
Long-Term Time-Sensitive Costs for CRF-Based Tracking by Detection,
MOTC16(II: 43-51).
Springer DOI 1611
BibRef

Ding, Y.P.[Yi-Peng], Tang, J.T.[Jing-Tian],
Micro-Doppler Trajectory Estimation of Pedestrians Using a Continuous-Wave Radar,
GeoRS(52), No. 9, Sept 2014, pp. 5807-5819.
IEEE DOI 1407
CW radar BibRef

Yildiz, A.[Alparslan], Takemura, N.[Noriko], Hori, M.[Maiya], Iwai, Y.[Yoshio], Sato, K.[Kosuke],
Tracking People with Active Cameras Using Variable Time-Step Decisions,
IEICE(E97-D), No. 8, August 2014, pp. 2124-2130.
WWW Link. 1408
BibRef
Earlier: A1, A2, A4, A5, Only:
Regression Based Trajectory Learning and Prediction for Human Motion,
PSIVTWS13(193-202).
Springer DOI 1402
BibRef

Chen, S.[Si], Li, S.Z.[Shao-Zi], Su, S.Z.[Song-Zhi], Cao, D.L.[Dong-Lin], Ji, R.R.[Rong-Rong],
Online semi-supervised compressive coding for robust visual tracking,
JVCIR(25), No. 5, 2014, pp. 793-804.
Elsevier DOI 1406
Visual tracking BibRef

Yuan, D.D.[De-Dong], Dong, J.[Jie], Su, S.Z.[Song-Zhi], Li, S.Z.[Shao-Zi], Ji, R.R.[Rong-Rong],
Pursuing Detector Efficiency for Simple Scene Pedestrian Detection,
MMMod14(II: 140-150).
Springer DOI 1405
BibRef

Shuai, B.[Bing], Su, S.Z.[Song-Zhi], Li, S.Z.[Shao-Zi], Cheng, Y.[Yun], Ji, R.R.[Rong-Rong],
Decomposed human localization in personal photo albums,
VCIP13(1-6)
IEEE DOI 1402
image retrieval BibRef

Sun, S.L.[Shi-Liang], Zhao, J.[Jing], Gao, Q.B.[Qing-Bin],
Modeling and recognizing human trajectories with beta process hidden Markov models,
PR(48), No. 8, 2015, pp. 2407-2417.
Elsevier DOI 1505
Human activity recognition BibRef

Shao, Z.P.[Zhan-Peng], Li, Y.F.[You-Fu],
Integral invariants for space motion trajectory matching and recognition,
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On-Road Pedestrian Tracking Across Multiple Driving Recorders,
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IEEE DOI 1509
data visualisation BibRef

Feng, Y., Ji, M., Xiao, J., Yang, X., Zhang, J.J., Zhuang, Y., Li, X.,
Mining Spatial-Temporal Patterns and Structural Sparsity for Human Motion Data Denoising,
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IEEE DOI 1512
Dictionaries BibRef

Shen, X.W.[Xue-Wei], Sui, X.B.[Xiu-Bao], Pan, K.[Kechen], Tao, Y.R.[Yuan-Rong],
Adaptive pedestrian tracking via patch-based features and spatial-temporal similarity measurement,
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Pedestrian tracking BibRef

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Hybrid 3D-2D human tracking in a top view,
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GbLN-PSO and Model-Based Particle Filter Approach for Tracking Human Movements in Large View Cases,
CirSysVideo(26), No. 8, August 2016, pp. 1433-1446.
IEEE DOI 1609
image motion analysis BibRef

Lee, K.H., Hwang, J.N., Okopal, G., Pitton, J.,
Ground-Moving-Platform-Based Human Tracking Using Visual SLAM and Constrained Multiple Kernels,
ITS(17), No. 12, December 2016, pp. 3602-3612.
IEEE DOI 1612
Cameras BibRef

Zhang, X.G.[Xu-Guang], Zhang, X.F.[Xu-Feng], Wang, Y.M.[Yi-Ming], Yu, H.[Hui],
Extended social force model-based mean shift for pedestrian tracking under obstacle avoidance,
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Liu, C., Fujishiro, R., Christopher, L., Zheng, J.,
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Bicycles BibRef

Lee, J.M.[Jae Moon], Kim, S.D.[Seong-Dong],
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Probabilistic multi-person localisation and tracking in image sequences,
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Examining pedestrian evasive actions as a potential indicator for traffic conflicts,
IET-ITS(11), No. 5, June 2017, pp. 282-289.
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A Novel Vision-Based Tracking Algorithm for a Human-Following Mobile Robot,
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IEEE DOI 1706
Cameras, Robot vision systems, Robustness, Target tracking, Visualization, Feedback linearization, K-D tree, Kalman filter, out-of-plane rotations, speeded up robust feature (SURF)-based human tracking, visual, servo, controller BibRef

Gupta, M.[Meenakshi], Garg, S.[Sourav], Kumar, S.[Swagat], Behera, L.[Laxmidhar],
An on-line visual human tracking algorithm using SURF-based dynamic object model,
ICIP13(3875-3879)
IEEE DOI 1402
Auto-regression prediction; Human Tracking; SURF BibRef

Watanabe, T.[Takuya], Akiyama, M.[Mitsuaki], Mori, T.[Tatsuya],
Tracking the Human Mobility Using Mobile Device Sensors,
IEICE(E100-D), No. 8, August 2017, pp. 1680-1690.
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Jiang, W.C.[Wen-Chao], Yin, Z.Z.[Zhao-Zheng],
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Guo, G.Y.[Guang-Yi], Chen, R.Z.[Rui-Zhi], Ye, F.[Feng], Chen, L.[Liang], Pan, Y.J.[Yuan-Jin], Liu, M.Y.[Meng-Yun], Cao, Z.P.[Zhi-Peng],
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IEEE DOI 1904
Target tracking, Detectors, Feature extraction, Visualization, Market research, Markov processes, Tracking-by-detection, people detection BibRef

Zhu, J.[Jiasong], Chen, S.Y.[Si-Yuan], Tu, W.[Wei], Sun, K.[Ke],
Tracking and Simulating Pedestrian Movements at Intersections Using Unmanned Aerial Vehicles,
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Pedestrian Path, Pose, and Intention Prediction Through Gaussian Process Dynamical Models and Pedestrian Activity Recognition,
ITS(20), No. 5, May 2019, pp. 1803-1814.
IEEE DOI 1905
Trajectory, Roads, Feature extraction, Hidden Markov models, Predictive models, Data mining, Europe, Pedestrians, pose prediction BibRef

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SIViP(13), No. 8, November 2019, pp. 1469-1476.
Springer DOI 1911
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PedPIV: Pedestrian Velocity Extraction From Particle Image Velocimetry,
ITS(21), No. 2, February 2020, pp. 580-589.
IEEE DOI 2002
Correlation, Optical imaging, Optical sensors, Legged locomotion, Aerodynamics, Tracking, Mathematical model, pedestrian traffic planning BibRef

Peng, S.Y.[Shi-Yu], Su, T.L.[Ting-Li], Jin, X.[Xuebo], Kong, J.L.[Jian-Lei], Bai, Y.T.[Yu-Ting],
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Time, Spatial, and Descriptive Features of Pedestrian Tracks on Set of Visualizations,
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Kwolek, B.[Bogdan], Rymut, B.[Boguslaw],
Reconstruction of 3D human motion in real-time using particle swarm optimization with GPU-accelerated fitness function,
RealTimeIP(17), No. 4, August 2020, pp. 821-838.
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Mixing Graphics and Compute for Real-Time Multiview Human Body Tracking,
ICCVG14(534-541).
Springer DOI 1410
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Trelinski, J.[Jacek], Kwolek, B.[Bogdan],
Convolutional Neural Network-Based Action Recognition on Depth Maps,
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Damotharasamy, S.[Sangeetha],
Approach to model human appearance based on sparse representation for human tracking in surveillance,
IET-IPR(14), No. 11, September 2020, pp. 2383-2394.
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Feng, W., Lan, L., Luo, Y., Yu, Y., Zhang, X., Luo, Z.,
Near-Online Multi-Pedestrian Tracking via Combining Multiple Consistent Appearance Cues,
CirSysVideo(31), No. 4, April 2021, pp. 1540-1554.
IEEE DOI 2104
Adaptation models, Trajectory, Computational modeling, Tracking, Data models, Integrated circuit modeling, focal triplet loss BibRef

Tsai, T.H.[Tsung-Han], Yao, C.H.[Chia-Hsiang],
A robust tracking algorithm for a human-following mobile robot,
IET-IPR(15), No. 3, 2021, pp. 786-796.
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Wang, H.S.[Hong-Song], Dong, J.[Jian], Cheng, B.[Bin], Feng, J.S.[Jia-Shi],
PVRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction,
IP(30), 2021, pp. 6096-6106.
IEEE DOI 2107
Hidden Markov models, Quaternions, Predictive models, Decoding, Dynamics, Recurrent neural networks, Human motion prediction, quaternion transformation BibRef

Wang, H.S.[Hong-Song], Wang, L.[Liang], Feng, J.S.[Jia-Shi], Zhou, D.Q.[Da-Quan],
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Human motion prediction, Action anticipation BibRef

Men, Q.H.[Qian-Hui], Ho, E.S.L.[Edmond S. L.], Shum, H.P.H.[Hubert P. H.], Leung, H.[Howard],
A Quadruple Diffusion Convolutional Recurrent Network for Human Motion Prediction,
CirSysVideo(31), No. 9, September 2021, pp. 3417-3432.
IEEE DOI 2109
Dynamics, Predictive models, Adaptation models, Hidden Markov models, Computational modeling, bi-directional predictor BibRef

Neogi, S.[Satyajit], Hoy, M.[Michael], Dang, K.[Kang], Yu, H.[Hang], Dauwels, J.[Justin],
Context Model for Pedestrian Intention Prediction Using Factored Latent-Dynamic Conditional Random Fields,
ITS(22), No. 11, November 2021, pp. 6821-6832.
IEEE DOI 2112
Hidden Markov models, Predictive models, Dynamics, Vehicle dynamics, Context modeling, Safety, Task analysis, conditional random fields BibRef

Csönde, G.[Gergely], Sekimoto, Y.[Yoshihide], Kashiyama, T.[Takehiro],
Online real-time pedestrian tracking from medium altitude aerial footage with camera motion cancellation,
CVIU(217), 2022, pp. 103386.
Elsevier DOI 2203
Remote sensing, Helicopter footage, Deep learning, Computer vision, Online tracking, Camera motion BibRef

Zhang, J.[Jian], Wang, J.[Jian], Cui, X.[Ximin], Yuan, D.[Debao],
BDS/GPS/UWB Adaptively Robust EKF Tightly Coupled Navigation Model Considering Pedestrian Motion Characteristics,
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DOI Link 2205
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Cai, Y.F.[Ying-Feng], Dai, L.[Lei], Wang, H.[Hai], Chen, L.[Long], Li, Y.C.[Yi-Cheng], Sotelo, M.A.[Miguel Angel], Li, Z.X.[Zhi-Xiong],
Pedestrian Motion Trajectory Prediction in Intelligent Driving from Far Shot First-Person Perspective Video,
ITS(23), No. 6, June 2022, pp. 5298-5313.
IEEE DOI 2206
Task analysis, Predictive models, Cameras, Trajectory, Legged locomotion, Training, Adaptation models, circular training BibRef

Xie, P.Y.[Peng-Yu], Xu, X.[Xin], Wang, Z.[Zheng], Yamasaki, T.[Toshihiko],
Sampling and Re-Weighting: Towards Diverse Frame Aware Unsupervised Video Person Re-Identification,
MultMed(24), 2022, pp. 4250-4261.
IEEE DOI 2210
Noise measurement, Target tracking, Training, Task analysis, Mars, Data models, Clustering, re-identification, unsupervised BibRef

Vial, A.[Alphonse], Hendeby, G.[Gustaf], Daamen, W.[Winnie], van Arem, B.[Bart], Hoogendoorn, S.[Serge],
Framework for Network-Constrained Tracking of Cyclists and Pedestrians,
ITS(24), No. 3, March 2023, pp. 3282-3296.
IEEE DOI 2303
Target tracking, Roads, Robot sensing systems, Bayes methods, Trajectory, Surveillance, Noise measurement, Pedestrians, cyclists, traffic monitoring and control BibRef

Wang, H.H.[Huan-Huan], Jin, L.S.[Li-Sheng], He, Y.[Yang], Huo, Z.[Zhen], Wang, G.Q.[Guang-Qi], Sun, X.Y.[Xin-Yu],
Detector-Tracker Integration Framework for Autonomous Vehicles Pedestrian Tracking,
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Zhang, X.X.[Xiao-Xiong], Ghimire, A.[Adarsh], Javed, S.[Sajid], Dias, J.[Jorge], Werghi, N.[Naoufel],
Robot-Person Tracking in Uniform Appearance Scenarios: A New Dataset and Challenges,
HMS(53), No. 3, June 2023, pp. 549-559.
IEEE DOI 2306
Robots, Target tracking, Robot kinematics, Benchmark testing, Visualization, Recording, Video sequences, RGB-D benchmark dataset BibRef

Zhang, X.[Xiao], Wang, Q.L.[Qi-Lin], Ye, Z.M.[Zi-Ming], Ying, H.C.[Hao-Chao], Yu, D.X.[Dong-Xiao],
Federated Representation Learning With Data Heterogeneity for Human Mobility Prediction,
ITS(24), No. 6, June 2023, pp. 6111-6122.
IEEE DOI 2306
Servers, Federated learning, Trajectory, Representation learning, Predictive models, Data models, Convolution, graph neural network BibRef

Xu, X.Y.[Xin-Yu], Li, Y.L.[Yong-Lu], Lu, C.W.[Ce-Wu],
Dynamic Context Removal: A General Training Strategy for Robust Models on Video Action Predictive Tasks,
IJCV(131), No. 12, December 2023, pp. 3272-3288.
Springer DOI 2311
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Sun, J.H.[Jian-Hua], Li, Y.X.[Yu-Xuan], Chai, L.[Liang], Fang, H.S.[Hao-Shu], Li, Y.L.[Yong-Lu], Lu, C.W.[Ce-Wu],
Human Trajectory Prediction with Momentary Observation,
CVPR22(6457-6466)
IEEE DOI 2210
Tracking, Navigation, Social robots, Predictive models, Feature extraction, Trajectory, Motion and tracking, Navigation and autonomous driving BibRef

Wang, F.[Feng], Ni, W.C.[Wei-Chuan], Liu, S.J.[Shao-Jiang], Xu, Z.M.[Zhi-Ming], Wan, Z.P.[Zhi-Ping],
An Intelligent Pedestrian Tracking Algorithm Based on Sparse Models in Urban Road Scene,
ITS(25), No. 3, March 2024, pp. 3064-3073.
IEEE DOI 2405
Pedestrians, Target tracking, Feature extraction, Dictionaries, Classification algorithms, Signal processing algorithms, model update mechanism BibRef

Yang, S.[Shubo], Li, H.[Haolun], Pun, C.M.[Chi-Man], Du, C.[Chun], Gao, H.[Hao],
Adaptive Spatial-Temporal Graph-Mixer for Human Motion Prediction,
SPLetters(31), 2024, pp. 1244-1248.
IEEE DOI 2405
Skeleton, Feature extraction, Convolution, Topology, Correlation, Prediction algorithms, Adaptive systems, Adaptive learning, graph convolution BibRef

Jin, C.J.[Cheng-Jie], Luo, Y.[Yuanwei], Wu, C.Y.[Chen-Yang], Song, Y.C.[Yu-Chen], Li, D.W.[Da-Wei],
Exploring the Pedestrian Route Choice Behaviors by Machine Learning Models,
IJGI(13), No. 5, 2024, pp. 146.
DOI Link 2405
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Mao, C.[Chen], Tan, C.[Chong], Hu, J.Q.[Jing-Qi], Zheng, M.[Min],
Time-Frequency Analysis of Variable-Length WiFi CSI Signals for Person Re-Identification,
SPLetters(31), 2024, pp. 2285-2289.
IEEE DOI 2410
Wireless fidelity, Time-frequency analysis, Feature extraction, Data models, Vectors, Training, Security, Person re-identification, feature fusion BibRef


Medina, E.[Edgar], Loh, L.[Leyong], Gurung, N.[Namrata], Oh, K.H.[Kyung Hun], Heller, N.[Niels],
Context-based Interpretable Spatio-Temporal Graph Convolutional Network for Human Motion Forecasting,
WACV24(3220-3229)
IEEE DOI 2404
Solid modeling, Analytical models, Predictive models, Robustness, Spatiotemporal phenomena, Safety, Algorithms, 3D computer vision, Autonomous Driving BibRef

Khan, S.[Salman], Teeti, I.[Izzeddin], Bradley, A.[Andrew], Elhoseiny, M.[Mohamed], Cuzzolin, F.[Fabio],
A Hybrid Graph Network for Complex Activity Detection in Video,
WACV24(6748-6758)
IEEE DOI 2404
Training, Analytical models, Uncertainty, Roads, Feature extraction, Algorithms, Video recognition and understanding, Algorithms, Autonomous Driving BibRef

Teeti, I.[Izzeddin], Bhargav, R.S.[Rongali Sai], Singh, V.[Vivek], Bradley, A.[Andrew], Banerjee, B.[Biplab], Cuzzolin, F.[Fabio],
Temporal DINO: A Self-supervised Video Strategy to Enhance Action Prediction,
ROAD++23(3273-3283)
IEEE DOI Code:
WWW Link. 2401
action prediction. DINO: self-distillation with no labels. BibRef

Chen, L.H.[Ling-Hao], Zhang, J.W.[Jia-Wei], Li, Y.[Yewen], Pang, Y.[Yiren], Xia, X.B.[Xiao-Bo], Liu, T.L.[Tong-Liang],
HumanMAC: Masked Motion Completion for Human Motion Prediction,
ICCV23(9510-9521)
IEEE DOI Code:
WWW Link. 2401
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Zhu, W.T.[Wen-Tao], Ma, X.X.[Xiao-Xuan], Liu, Z.Y.[Zhao-Yang], Liu, L.[Libin], Wu, W.[Wayne], Wang, Y.Z.[Yi-Zhou],
MotionBERT: A Unified Perspective on Learning Human Motion Representations,
ICCV23(15039-15053)
IEEE DOI Code:
WWW Link. 2401
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Yuan, Y.[Ye], Song, J.[JiaMing], Iqbal, U.[Umar], Vahdat, A.[Arash], Kautz, J.[Jan],
PhysDiff: Physics-Guided Human Motion Diffusion Model,
ICCV23(15964-15975)
IEEE DOI 2401
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Eisl, D.[Dominik], Herzog, F.[Fabian], Dugelay, J.L.[Jean-Luc], Apvrille, L.[Ludovic], Rigoll, G.[Gerhard],
Introducing A Framework for Single-Human Tracking Using Event-Based Cameras,
ICIP23(3269-3273)
IEEE DOI 2312
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Wang, T.[Tsaipei], Chiang, S.H.[Sheng-Ho],
Online Pedestrian Tracking Using A Dense Fisheye Camera Network With Edge Computing,
ICIP23(3518-3522)
IEEE DOI 2312
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Tiwari, A.[Amogh], Manu, P.[Pranav], Rathore, N.[Nakul], Srivastava, A.[Astitva], Sharma, A.[Avinash],
ConVol-E: Continuous Volumetric Embeddings for Human-Centric Dense Correspondence Estimation,
IMW23(6187-6195)
IEEE DOI 2309
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Nguyen, Q.Q.V.[Quang Qui-Vinh], Le, H.D.A.[Huy Dinh-Anh], Chau, T.T.T.[Truc Thi-Thanh], Luu, D.T.[Duc Trung], Chung, N.M.[Nhat Minh], Ha, S.V.U.[Synh Viet-Uyen],
Multi-camera People Tracking With Mixture of Realistic and Synthetic Knowledge,
AICity23(5496-5506)
IEEE DOI 2309
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Guo, W.[Wen], Du, Y.M.[Yu-Ming], Shen, X.[Xi], Lepetit, V.[Vincent], Alameda-Pineda, X.[Xavier], Moreno-Noguer, F.[Francesc],
Back to MLP: A Simple Baseline for Human Motion Prediction,
WACV23(4798-4808)
IEEE DOI 2302
Training, Recurrent neural networks, Deep architecture, Transformers, Discrete cosine transforms, 3D computer vision BibRef

Das, D.[Dipankar], Miura, J.[Jun],
Camera Motion Compensation and Person Detection in Construction Site Using Yolo-Bayes Model,
ICPR22(4566-4572)
IEEE DOI 2212
Training, Cranes, Motion estimation, Cameras, Motion compensation, Bayes methods, Yolo-Bayes model, person detection BibRef

Lucas, T.[Thomas], Baradel, F.[Fabien], Weinzaepfel, P.[Philippe], Rogez, G.[Grégory],
PoseGPT: Quantization-Based 3D Human Motion Generation and Forecasting,
ECCV22(VI:417-435).
Springer DOI 2211
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Agudo, A.[Antonio],
Spline Human Motion Recovery,
ICIP22(4138-4142)
IEEE DOI 2211
Surface reconstruction, Shape, Computational modeling, Cameras, Trajectory, Splines (mathematics), Optimization, 4D Reconstruction, Optimization BibRef

Xu, P.[Pei], Hayet, J.B.[Jean-Bernard], Karamouzas, I.[Ioannis],
SocialVAE: Human Trajectory Prediction Using Timewise Latents,
ECCV22(IV:511-528).
Springer DOI 2211
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Henning, D.F.[Dorian F.], Laidlow, T.[Tristan], Leutenegger, S.[Stefan],
BodySLAM: Joint Camera Localisation, Mapping, and Human Motion Tracking,
ECCV22(XXIX:656-673).
Springer DOI 2211
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Gong, D.[Dayoung], Lee, J.[Joonseok], Kim, M.[Manjin], Ha, S.J.[Seong Jong], Cho, M.[Minsu],
Future Transformer for Long-term Action Anticipation,
CVPR22(3042-3051)
IEEE DOI 2210
Visualization, Neural networks, Predictive models, Benchmark testing, Transformers, Decoding, Action and event recognition BibRef

Mao, W.[Wei], Liu, M.M.[Miao-Miao], Salzmann, M.[Mathieu],
Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction,
CVPR22(8141-8150)
IEEE DOI 2210
Training, Stochastic processes, Training data, Predictive models, Transformers, Encoding, Trajectory, Motion and tracking, Action and event recognition BibRef

Bae, I.[Inhwan], Park, J.H.[Jin-Hwi], Jeon, H.G.[Hae-Gon],
Non-Probability Sampling Network for Stochastic Human Trajectory Prediction,
CVPR22(6467-6477)
IEEE DOI 2210
Codes, Computational modeling, Computer network reliability, Stochastic processes, Benchmark testing, Probabilistic logic, Robot vision BibRef

Xu, C.X.[Chen-Xin], Mao, W.[Weibo], Zhang, W.J.[Wen-Jun], Chen, S.[Siheng],
Remember Intentions: Retrospective-Memory-based Trajectory Prediction,
CVPR22(6478-6487)
IEEE DOI 2210
Training, Tracking, Navigation, Memory architecture, Training data, Predictive models, Trajectory, Motion and tracking, Navigation and autonomous driving BibRef

Faure, B.[Benoît], Odic, N.[Nathan], Haggui, O.[Olfa], Magnier, B.[Baptiste],
Performance of Recent Tiny/Small YOLO Versions in the Context of Top-View Fisheye Images,
ISHAPE22(246-257).
Springer DOI 2208
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Mancusi, G.[Gianluca], Fabbri, M.[Matteo], Egidi, S.[Sara], Verasani, M.[Mattia], Scarabelli, P.[Paolo], Calderara, S.[Simone], Cucchiara, R.[Rita],
First Steps Towards 3D Pedestrian Detection and Tracking from Single Image,
CIAP22(II:335-346).
Springer DOI 2205
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Fabbri, M.[Matteo], Brasó, G.[Guillem], Maugeri, G.[Gianluca], Cetintas, O.[Orcun], Gasparini, R.[Riccardo], Ošep, A.[Aljoša], Calderara, S.[Simone], Leal-Taixé, L.[Laura], Cucchiara, R.[Rita],
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?,
ICCV21(10829-10839)
IEEE DOI 2203
Training, Learning systems, Roads, Training data, Object detection, Manuals, Motion and tracking, BibRef

Specker, A.[Andreas], Beyerer, J.[Jürgen],
Improving Attribute-Based Person Retrieval By Using A Calibrated, Weighted, and Distribution-Based Distance Metric,
ICIP21(2378-2382)
IEEE DOI 2201
Measurement, Biometrics (access control), Surveillance, Image processing, Euclidean distance, Calibration, retrieval, re-identification BibRef

Wang, C.X.[Chen-Xi], Wang, Y.F.[Yun-Feng], Huang, Z.X.[Zi-Xuan], Chen, Z.W.[Zhi-Wen],
Simple Baseline for Single Human Motion Forecasting,
SoMoF21(2260-2265)
IEEE DOI 2112
Training, Visualization, Computational modeling, Benchmark testing, Trajectory BibRef

Peng, Y.S.[Yu-Sheng], Zhang, G.F.[Gao-Feng], Li, X.Y.[Xiang-Yu], Zheng, L.P.[Li-Ping],
STIRNet: A Spatial-temporal Interaction-aware Recursive Network for Human Trajectory Prediction,
SoMoF21(2285-2293)
IEEE DOI 2112
Measurement, Uncertainty, Computational modeling, Predictive models, Trajectory BibRef

Shafiee, N.[Nasim], Padir, T.[Taskin], Elhamifar, E.[Ehsan],
Introvert: Human Trajectory Prediction via Conditional 3D Attention,
CVPR21(16810-16820)
IEEE DOI 2111
Visualization, Solid modeling, Computational modeling, Predictive models, Trajectory, Computational efficiency BibRef

Chen, L., Wu, B., Zhao, Y.,
A Real-time Photogrammetric System for Monitoring Human Movement Dynamics,
ISPRS20(B2:561-566).
DOI Link 2012
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Mrabti, W., Bellach, B., Morain-Nicolier, F., Tairi, H.,
Tracking a human being via the gray local dissimilarity map,
ISCV20(1-6)
IEEE DOI 2011
image filtering, image sequences, Kalman filters, object tracking, gray local dissimilarity map, Kalman Filter BibRef

Cao, Z.[Zhe], Gao, H.[Hang], Mangalam, K.[Karttikeya], Cai, Q.Z.[Qi-Zhi], Vo, M.[Minh], Malik, J.[Jitendra],
Long-term Human Motion Prediction with Scene Context,
ECCV20(I:387-404).
Springer DOI 2011
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CVPR20(12141-12150)
IEEE DOI 2008
Cameras, Measurement, Adaptation models, Data privacy, Data models, Machine learning, Computer vision BibRef

Zeng, K., Ning, M., Wang, Y., Guo, Y.,
Hierarchical Clustering With Hard-Batch Triplet Loss for Person Re-Identification,
CVPR20(13654-13662)
IEEE DOI 2008
Training, Merging, Adaptation models, Supervised learning, Distance measurement, Optimization, Cameras BibRef

Zhang, Z.S.[Zhi-Shuai], Gao, J.Y.[Ji-Yang], Mao, J.H.[Jun-Hua], Liu, Y.K.[Yu-Kai], Anguelov, D.[Dragomir], Li, C.C.[Cong-Cong],
STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction,
CVPR20(11343-11352)
IEEE DOI 2008
Trajectory, Proposals, Feature extraction, Task analysis, Object detection, Detectors BibRef

Saini, N., Price, E., Tallamraju, R., Enficiaud, R., Ludwig, R., Martinovic, I., Ahmad, A., Black, M.,
Markerless Outdoor Human Motion Capture Using Multiple Autonomous Micro Aerial Vehicles,
ICCV19(823-832)
IEEE DOI 2004
autonomous aerial vehicles, calibration, cameras, Global Positioning System, image capture, image colour analysis, Shape BibRef

Bi, H., Fang, Z., Mao, T., Wang, Z., Deng, Z.,
Joint Prediction for Kinematic Trajectories in Vehicle-Pedestrian-Mixed Scenes,
ICCV19(10382-10391)
IEEE DOI 2004
image motion analysis, image representation, object tracking, pedestrians, recurrent neural nets, road traffic, Anomaly detection BibRef

Kotseruba, I.[Iuliia], Rasouli, A.[Amir], Tsotsos, J.K.[John K.],
Benchmark for Evaluating Pedestrian Action Prediction,
WACV21(1257-1267)
IEEE DOI 2106
Convolutional codes, Training, Solid modeling, Protocols, Computational modeling, Benchmark testing BibRef

Rasouli, A., Kotseruba, I., Kunic, T., Tsotsos, J.K.[John K.],
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ICCV19(6261-6270)
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Huang, Y., Bi, H., Li, Z., Mao, T., Wang, Z.,
STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction,
ICCV19(6271-6280)
IEEE DOI 2004
image motion analysis, image sequences, object detection, pedestrians, traffic engineering computing, video surveillance, Dynamics BibRef

Kulkarni, P.[Pratik], Mohan, S.[Shrey], Rogers, S.[Samuel], Tabkhi, H.[Hamed],
Key-Track: A Lightweight Scalable LSTM-based Pedestrian Tracker for Surveillance Systems,
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Evaluation of CNN for predicting pedestrian paths. BibRef

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cameras, learning (artificial intelligence), neural nets, object detection, pedestrians, stereo image processing, R200 BibRef

Dehzangi, O., Bache, B.A., Iftikhar, O.,
Activity Detection using Fusion of Multi-Pressure Sensors in Insoles,
ICPR18(3315-3321)
IEEE DOI 1812
Sensor fusion, Pressure sensors, Feature extraction, Legged locomotion, Monitoring, Fractals BibRef

Zhou, X., Chen, K., Zhou, Q.,
Human tracking by employing the scene information in underground coal mines,
VCIP17(1-4)
IEEE DOI 1804
image filtering, image sequences, learning (artificial intelligence), mining, object detection, underground coal mine BibRef

Jiang, Z.Q.[Zheng-Qiang], Huynh, D.Q.[Du Q.], Zhang, J.[Jian], Wu, Q.[Qiang],
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DICTA17(1-8)
IEEE DOI 1804
Deformable part model. Bayes methods, image colour analysis, image fusion, image representation, image sequences, object detection, Target tracking BibRef

Liu, C., Huynh, D.Q., Reynolds, M.,
Learning Variance Kernelized Correlation Filters for Robust Visual Object Tracking,
DICTA17(1-8)
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filtering theory, learning (artificial intelligence), object detection, Visualization BibRef

Shah, P.[Parshwa], Garg, A.[Arpit], Gajjar, V.[Vandit],
PeR-ViS: Person Retrieval in Video Surveillance using Semantic Description,
WACVW21(41-50) Activity Detection
IEEE DOI 2105
Image segmentation, Image color analysis, Filtering, Semantics, Video surveillance BibRef

Gajjar, V., Khandhediya, Y., Gurnani, A.,
Human Detection and Tracking for Video Surveillance: A Cognitive Science Approach,
CogCV17(2805-2809)
IEEE DOI 1802
Clustering algorithms, Computational modeling, Feature extraction, Prediction algorithms, Visualization BibRef

Boschini, M., Poggi, M., Mattoccia, S.,
Improving the reliability of 3D people tracking system by means of deep-learning,
IC3D16(1-8)
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cameras BibRef

Häger, G.[Gustav], Bhat, G.[Goutam], Danelljan, M.[Martin], Khan, F.S.[Fahad Shahbaz], Felsberg, M.[Michael], Rudl, P.[Piotr], Doherty, P.[Patrick],
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Ray, L.[Laura], Miao, T.S.[Tian-Shun],
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Nguyen, T.L.A., Bremond, F., Trojanova, J.,
Multi-object tracking of pedestrian driven by context,
AVSS16(23-29)
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Ramadan, H., Tairi, H.,
Automatic Human Segmentation in Video Using Convex Active Contours,
CGiV16(184-189)
IEEE DOI 1608
convex programming BibRef

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WACV16(1-9)
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ICCVIA15(1-4)
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cameras BibRef

Varga, D., Szirányi, T.[Tamás], Kiss, A., Sporas, L., Havasi, L.[László],
A Multi-View Pedestrian Tracking Method in an Uncalibrated Camera Network,
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CIAP15(II:620-630).
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AVSS16(194-199)
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Greco, L., Ritrovato, P.[Pierluigi], Saggese, A.[Alessia], Vento, M.[Mario],
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PETS16(1297-1304)
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Gaüzère, B.[Benoit], Ritrovato, P.[Pierluigi], Saggese, A.[Alessia], Vento, M.[Mario],
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Ioannidis, D., Krinidis, S., Tzovaras, D., Likothanassis, S.,
Human tracking & visual spatio-temporal statistical analysis,
ICIP14(3417-3419)
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ECCV14(VI: 618-633).
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Mutlu, S.[Sinan], Hu, T.[Tao], Lanz, O.[Oswald],
Learning the Scene Illumination for Color-Based People Tracking in Dynamic Environment,
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Godil, A.[Afzal], Bostelman, R.[Roger], Saidi, K.[Kamel], Shackleford, W.[Will], Cheok, G.[Geraldine], Shneier, M.[Michael], Hong, T.[Tsai],
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GT13(719-726)
IEEE DOI 1309
Ground-Truth Systems BibRef

Fan, Z.[Zipei], Wang, Z.[Zeliang], Cui, J.S.[Jin-Shi], Davoine, F.[Franck], Zhao, H.J.[Hui-Jing], Zha, H.B.[Hong-Bin],
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Ali, A., Terada, K.,
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Yi, O.Y.[Ou-Yang], Yun, L.[Ling], Xing, J.G.[Jian-Guo],
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Sheikh, Y.A.[Yaser Ajmal], Datta, A.[Ankur], Kanade, T.[Takeo],
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FG08(1-7).
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Yamashita, T.[Takayoshi], Fujiyoshi, H.[Hironobu], Lao, S.H.[Shi-Hong], Kawade, M.[Masato],
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ICPR08(1-4).
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Tsuduki, Y.J.[Yu-Ji], Fujiyoshi, H.[Hironobu],
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PSIVT09(25-36).
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Shah, S.K.[Shishir K.],
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AVSBS08(268-269).
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Nicolescu, M.[Mircea],
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AVSBS08(36-37).
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See also Dynamic Models for People Detection and Tracking. BibRef

Tung, T.[Tony], Matsuyama, T.[Takashi],
Human motion tracking using a color-based particle filter driven by optical flow,
MLMotion08(xx-yy). 0810
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Ji, J.W.[Jing-Wei], Buch, S.[Shyamal], Soto, A.[Alvaro], Niebles, J.C.[Juan Carlos],
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ECCV18(II: 734-749).
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Qian, Y.J.[Yi-Jun], Yu, L.J.[Li-Jun], Liu, W.H.[Wen-He], Hauptmann, A.G.[Alexander G.],
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WACVWS20(126-133)
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Proposals, Feature extraction, Surveillance, Object detection, Trajectory, Graphics processing units, Cameras BibRef

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ECCV08(IV: 527-540).
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Niebles, J.C.[Juan Carlos], Han, B.H.[Bo-Hyung], Fei-Fei, L.[Li],
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CVPR10(655-662).
IEEE DOI 1006
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Miller, A.[Andrew], Basharat, A.[Arslan], White, B.[Brandyn], Liu, J.G.[Jin-Gen], Shah, M.[Mubarak],
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Miller, A.[Andrew], Babenko, P.[Pavel], Hu, M.[Min], Shah, M.[Mubarak],
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Gallagher, A.C.[Andrew C.], Chen, T.H.[Tsu-Han],
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Ren, X.F.[Xiao-Feng],
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ICCV07(1-8).
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Pflugfelder, R.[Roman], Bischof, H.[Horst],
Tracking across non-overlapping views via geometry,
ICPR08(1-4).
IEEE DOI 0812
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Earlier:
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AVSBS07(393-398).
IEEE DOI 0709
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Tong, M.[Minglei], Liu, Y.C.[Yun-Cai],
Shared Latent Dynamical Model for Human Tracking from Videos,
MCAM07(102-111).
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Shivappa, S.T.[Shankar T.], Trivedi, M.M.[Mohan M.], Rao, B.D.[Bhaskar D.],
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AVSBS08(260-267).
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Fihl, P., Corlin, R., Park, S., Moeslund, T.B., Trivedi, M.M.,
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Chen, X.[Xi], He, Z.H.[Zhi-Hai], Anderson, D., Keller, J.M., Skubic, M.,
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ICIP06(561-564).
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Taycher, L.[Leonid], Demirdjian, D.[David], Darrell, T.J.[Trevor J.], Shakhnarovich, G.[Gregory],
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Part Based Human Tracking In A Multiple Cues Fusion Framework,
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Siebel, N.T., Maybank, S.J.,
Fusion of Multiple Tracking Algorithms for Robust People Tracking,
ECCV02(IV: 373 ff.).
Springer DOI 0205
BibRef
Earlier:
Real-Time Tracking of Pedestrians and Vehicles,
PETS01(xx-yy). 0110
BibRef

Siebel, N.T.[Nils T],
Design and Implementation of People Tracking Algorithms for Visual Surveillance Applications,
Ph.D.Thesis, March 2003, Department of Computer Science, The University of Reading, Reading, UK.
PDF File. Code, Tracking.
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Bennewitz, M., Burgard, W., Cielniak, G.,
Utilizing Learned Motion Patterns to Robustly Track Persons,
PETS03(102-109). non-uniform time intervals allowed. BibRef 0300

Zhou, J.P.[Jian-Peng], Hoang, J.[Jack],
Real Time Robust Human Detection and Tracking System,
OTCBVS05(III: 149-149).
IEEE DOI 0507
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Latzel, M.[Markus], Darcourt, E.[Emilie], Tsotsos, J.K.[John K.],
People Tracking using Robust Motion Detection and Estimation,
CRV05(270-275).
IEEE DOI 0505
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Yelal, M.R., Sasi, S.,
Human tracking in real-time video for varying illumination,
AVSBS05(141-146).
IEEE DOI 0602
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Abdelkader, M.F.[Mohamed F.], Chellappa, R.[Rama], Zheng, Q.F.[Qin-Fen], Chan, A.L.[Alex L.],
Integrated Motion Detection and Tracking for Visual Surveillance,
CVS06(28).
IEEE DOI 0602
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Do, Y.T.[Yong-Tae],
Region Based Detection of Occluded People for the Tracking in Video Image Sequences,
CAIP05(829).
Springer DOI 0509
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Caillette, F., Howard, T.,
Real-Time Markerless Human Body Tracking with 3-D Voxel Reconstruction,
BMVC04(xx-yy).
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Roth, D.[Daniel], Doubek, P.[Petr], Van Gool, L.J.[Luc J.],
Bayesian Pixel Classification for Human Tracking,
Motion05(II: 78-83).
IEEE DOI 0502
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Govindaraju, D.[Dinesh], Browning, B.[Brett], Veloso, M.[Manuela],
Person Tracking from a Dynamic Balancing Platform,
CMU-CS-TR-04-181. 2004.
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Yang, M.T.[Mau-Tsuen], Shih, Y.C.[Ya-Chun], Wang, S.C.[Shih-Chun],
People tracking by integrating multiple features,
ICPR04(IV: 929-932).
IEEE DOI 0409
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Kettnaker, V.M.[Vera M.], Gahm, J.K.,
Closed-loop person tracking and detection,
CRV04(315-320).
IEEE DOI 0408
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Lan, X.Y.[Xiang-Yang], Huttenlocher, D.P.,
A unified spatio-temporal articulated model for tracking,
CVPR04(I: 722-729).
IEEE DOI
PDF File. 0408
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Demirdjian, D., Ko, T., Darrell, T.J.,
Constraining human body tracking,
ICCV03(1071-1078).
IEEE DOI 0311
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Merven, B.[Bruno], Nicolls, F.[Fred], de Jager, G.[Gerhard],
Auto Camera Calibration Method for Person Tracking Applications,
SCIA03(91-100).
Springer DOI 0310
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Luck, J.P., Debrunner, C.H., Hoff, W., He, Q., Small, D.E.,
Development and analysis of a real-time human motion tracking system,
WACV02(196-202).
IEEE DOI 0303
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Kang, J.M.[Jin-Man], Cohen, I., Medioni, G.,
Continuous multi-views tracking using tensor voting,
Motion02(181-186).
IEEE DOI 0303

See also Detection and Tracking of Moving Objects from Overlapping EO and IR Sensors. BibRef

Kang, E.Y.[Eun-Young], Cohen, I., Medioni, G.,
A robust and non-iterative estimation method of multiple 2d motions,
ICIP04(V: 3367-3370).
IEEE DOI
PDF File. 0505
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Earlier:
Robust affine motion estimation in joint image space using tensor voting,
ICPR02(IV: 256-259).
IEEE DOI
PDF File. 0211
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Jesus, R.M.[Rui M.], Abrantes, A.J.[Arnaldo J.], Marques, J.S.[Jorge S.],
Tracking the Human Body Using Multiple Predictors,
AMDO02(155 ff.).
Springer DOI 0303
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Farmer, M.E., Hsu, R.L.[Rein-Lien], Jain, A.K.,
Interacting multiple model (IMM) kalman filters for robust high speed human motion tracking,
ICPR02(II: 20-23).
IEEE DOI 0211
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Piau, N.K.[Ng Kim], Ranganath, S.,
Tracking people,
ICPR02(II: 370-373).
IEEE DOI 0211
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Zhao, H.X.[Hung-Xin], Huang, Y.S.[Yea-Shuan],
Real-time multiple-person tracking system,
ICPR02(II: 897-900).
IEEE DOI 0211
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Senior, A.W.,
Tracking People with Probabilistic Appearance Models,
PETS02(48-55). 0207
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Loy, G., Fletcher, L.S., Apostoloff, N., Zelinsky, A.,
An adaptive fusion architecture for target tracking,
AFGR02(248-253).
IEEE DOI 0206
BibRef

Plaenkers, R., Fua, P.,
Model-Based Silhouette Extraction for Accurate People Tracking,
ECCV02(II: 325 ff.).
Springer DOI 0205
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Fablet, R., Black, M.J.,
Automatic Detection and Tracking of Human Motion with a View-Based Representation,
ECCV02(I: 476 ff.).
Springer DOI 0205
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Kwatra, V.[Vivek], Bobick, A.F.[Aaron F.], Johnson, A.Y.[Amos Y.],
Temporal Integration of Multiple Silhouette-based Body-part Hypotheses,
CVPR01(II:758-764).
IEEE DOI 0110

See also Appearance-based Body Model for Multiple People Tracking, An. BibRef

Boyd, J.E.[Jeffrey E.], Sayles, M.[Maxwell],
Real-Time Video Phase-Locked Loops,
ICCV01(II: 742).
IEEE DOI 0106
BibRef

Poon, E., Fleet, D.J.,
Hybrid Monte Carlo filtering: Edge-based people tracking,
Motion02(151-158).
IEEE DOI 0303
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Choo, K.[Kiam], Fleet, D.J.[David J.],
People Tracking Using Hybrid Monte Carlo Filtering,
ICCV01(II: 321-328).
IEEE DOI 0106
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Stuart, B.V.[Bradley V.], Aloimonos, Y.F.[Yi-Fannis],
Ray Carving with Gradients and Motion,
HUMO00(81-87).
IEEE Top Reference. 0010
Tracking walking person. BibRef

Zhuang, Y., Zhu, Q., Pan, Y., Liu, X.,
Hierarchical Model Based Human Motion Tracking,
ICIP00(Vol III: 86-89).
IEEE DOI 0008
BibRef

Rajagopalan, A.N., Chellappa, R.,
Higher-order Spectral Analysis of Human Motion,
ICIP00(Vol III: 230-233).
IEEE DOI 0008
BibRef

Murakami, S.I., Wada, A.,
An Automatic Extraction and Display Method of Walking Person's Trajectories,
ICPR00(Vol IV: 611-614).
IEEE DOI 0009
BibRef

Bui, H.H., Venkatesh, S., West, G.A.W.,
A Probablistic Framework for Tracking in Wide-area Environments,
ICPR00(Vol IV: 702-705).
IEEE DOI 0009
BibRef

Sigal, L., Bhatia, S., Roth, S., Black, M.J., Isard, M.,
Tracking loose-limbed people,
CVPR04(I: 421-428).
IEEE DOI 0408
BibRef

Roth, S., Sigal, L., Black, M.J.,
Gibbs likelihoods for Bayesian tracking,
CVPR04(I: 886-893).
IEEE DOI 0408
BibRef

Yamamoto, M.[Masanobu], Yagishita, K.[Katsutoshi],
Scene Constraints-Aided Tracking of Human Body,
CVPR00(I: 151-156).
IEEE DOI 0005
Constraints help! BibRef

Heisele, B., Kressel, U., Ritter, W.,
Tracking Non-Rigid Moving Objects Based on Color Cluster Flow,
CVPR97(257-260).
IEEE DOI 9704
People walking; not feature tracking. BibRef

Kato, H.[Hirokazu], Inokuchi, S.[Seiji], Nakazawa, A.[Atsushi],
Human Tracking Using Distributed Vision Systems,
ICPR98(Vol I: 593-596).
IEEE DOI 9808
BibRef

Pingali, S.V.G.K.[Sarma V.G.K.], Segen, J.[Jakub],
Method and apparatus for tracking moving objects in real time using contours of the objects and feature paths,
US_Patent5,764,283, Jun 9, 1998
WWW Link. BibRef 9806

Segen, J.[Jakub],
Method and apparatus for tracking, storing, and synthesizing an animated version of object motion,
US_Patent6,072,504, Jun 6, 2000
WWW Link. BibRef 0006

Segen, J.[Jakub], Pingali, G.S.,
A Camera Based System for Tracking People in Real Time,
ICPR96(III: 63-67).
IEEE DOI 9608
(ATT Bell Laboratories, USA) BibRef

Pingali, G.S., and Segen, J.[Jakub],
Performance Evaluation of People Tracking Systems,
WACV96(33-38).
IEEE DOI 9609
BibRef

Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Pedestrian Trajectory Analysis, Pedestrian Tracking .


Last update:Oct 22, 2024 at 22:09:59