PETS Benchmark Datasets,
Online2006 Dataset:
HTML Version.
Dataset, Surveillance.
2014 Dataset:
HTML Version. 2015 Dataset:
HTML Version. 2016 Dataset:
HTML Version.
BibRef
0600
MIT Pedestrian Database MITP,
Online2000
HTML Version.
Dataset, Surveillance.
BibRef
0001
UCF Action Recogniton Dataset 101,
Online2012
WWW Link.
1211
BibRef
Earlier:
UCF Action Recogniton Dataset 50,
Online2010
WWW Link.
Dataset, Surveillance.
1010
101 action categories, consisting of realistic videos taken from youtube.
UCF 101 is an extension of UCF 50.
Categories include:
Baseball Pitch, Basketball Shooting, Bench Press, Biking, Biking,
Billiards Shot,Breaststroke, Clean and Jerk, Diving, Drumming,
Fencing, Golf Swing, Playing Guitar, High Jump, Horse Race, Horse
Riding, Hula Hoop, Javelin Throw, Juggling Balls, Jump Rope, Jumping
Jack, Kayaking, Lunges, Military Parade, Mixing Batter, Nun chucks,
Playing Piano, Pizza Tossing, Pole Vault, Pommel Horse, Pull Ups,
Punch, Push Ups, Rock Climbing Indoor, Rope Climbing, Rowing, Salsa
Spins, Skate Boarding, Skiing, Skijet, Soccer, Juggling, Swing,
Playing Tabla, TaiChi, Tennis Swing, Trampoline Jumping, Playing
Violin, Volleyball Spiking, Walking with a dog, and Yo Yo.
The printed reference:
See also UCF101: A Dataset of 101 Human Action Classes from Videos in The Wild.
BibRef
UCF-iPhone,
Online2012
WWW Link.
Dataset, Surveillance.
1203
Aerobic actions using the Inertial Measurement Unit (IMU) on an Apple iPhone.
Biking, Climbing Stairs, Descending Stairs, Gym Biking, Jump Roping,
Running, Standing, Treadmill Walking and Walking.
See also Macro-Class Selection for Hierarchical K-NN Classification of Inertial Sensor Data. for the paper.
BibRef
The KITTI Vision Benchmark Suite,
Online2013
WWW Link.
Dataset, Road Scenes.
Award, Everingham Prize. Stereo, Lidar, GPS, etc.
See also Vision meets robotics: The KITTI dataset.
BibRef
1300
Hollywood2 Human Actions and Scenes Dataset,
Online2016
WWW Link.
Dataset, Surveillance.
1608
Part originally from:
See also Actions in context.
BibRef
HMDB: a large human motion database,
Online2016
WWW Link.
Dataset, Surveillance.
Award, ICCV, Helmholtz.
1608
51 actions.
See also HMDB: A large video database for human motion recognition.
BibRef
TRECVID Workshop DAta,
Online2017
HTML Version.
Dataset, Surveillance.
1806
Surveillance datasets from 2001 to 2017.
BibRef
Privacy-Preserving Visual Recognition PA-HMDB51,
Online2019.
WWW Link.
Dataset, Actions.
Dataset, Privacy.
The dataset contains 592 videos selected from the HMDB51 dataset
(
See also HMDB: A large video database for human motion recognition. ).
For each video, we provide with frame-level annotation of five
privacy attributes: skin color, gender, face, nudity, and
relationship.
See also Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study.
BibRef
1900
HVU Dataset,
Online2021
WWW Link.
Dataset, Action. For Holistic Video Understanding workshop
BibRef
2100
EPIC-KITCHENS,
Online2018
WWW Link.
Dataset, Action.
Dataset, Daily Activities.
First-person (egocentric) vision; multi-faceted non-scripted
recordings in native environments - i.e. the wearers' homes, capturing
all daily activities in the kitchen over multiple days.
See also EPIC-KITCHENS Dataset: Collection, Challenges and Baselines, The.
BibRef
1800
Egocentric Live 4D Perception (Ego4D) Dataset:
A large-scale first-person video dataset, supporting research
in multi-modal machine perception for daily life activity,
Online2021
WWW Link.
Dataset, Action.
Dataset, Egocentric. The Ego4D Consortium.
A large-scale first-person video dataset, supporting research in
multi-modal machine perception for daily life activity.
BibRef
2100
Kay, W.[Will],
Carreira, J.[Joao],
Simonyan, K.[Karen],
Zhang, B.[Brian],
Hillier, C.[Chloe],
Vijayanarasimhan, S.[Sudheendra],
Viola, F.[Fabio],
Green, T.[Tim],
Back, T.[Trevor],
Natsev, P.[Paul],
Suleyman, M.[Mustafa],
Zisserman, A.[Andrew],
The Kinetics Human Action Video Dataset,
Online2019.
WWW Link.
WWW Link.
Dataset, Actions.
Dataset, Human Action.
BibRef
1900
Tenorth, M.[Moritz],
Bandouch, J.[Jan],
Beetz, M.[Michael],
The TUM Kitchen Data Set of everyday manipulation activities for motion
tracking and action recognition,
THEMIS09(1089-1096).
IEEE DOI
0910
Dataset, Activity Recognition.
BibRef
Johansson, G.,
Visual Motion Perception,
SciAmer(232), June 1976, pp. 75-88.
BibRef
7606
And:
Visual Perception of Biological Motion and a Model for
Its Analysis,
PandP(14), No. 2 1973, pp. 201-211.
The psychological references that human motion papers use.
BibRef
Badler, N.I., and
Smoliar, S.W.,
Digital Representations of Human Movement,
Surveys(11), No. 1, March 1979, pp. 19-38.
Survey, Motion, Human.
BibRef
7903
Calvert, T.W.,
Chapman, A.E.,
Analysis and Synthesis of Human Movement,
HPRIP-CV94(431-474).
BibRef
9400
Aggarwal, J.K.,
Cai, Q.,
Human Motion Analysis: A Review,
CVIU(73), No. 3, March 1999, pp. 428-440.
DOI Link
BibRef
9903
Gavrila, D.M.[Dariu M.],
The Visual Analysis of Human Movement: A Survey,
CVIU(73), No. 1, January 1999, pp. 82-98.
DOI Link
PDF File.
Survey, Human Motion.
BibRef
9901
Ivancevic, V.G.,
Snoswell, M.,
Fuzzy-stochastic functor machine for general humanoid-robot dynamics,
SMC-B(31), No. 3, June 2001, pp. 319-330.
IEEE Top Reference.
0108
BibRef
Wang, L.[Liang],
Hu, W.M.[Wei-Ming],
Tan, T.N.[Tie-Niu],
Recent developments in human motion analysis,
PR(36), No. 3, March 2003, pp. 585-601.
Elsevier DOI
0301
BibRef
Maybank, S.J.[Steve J.],
Tan, T.N.[Tie-Niu],
Introduction: Surveillance,
IJCV(37), No. 2, June 2000, pp. 173-173.
DOI Link
0008
BibRef
Maybank, S.J.,
Tan, T.N.,
Special Issue on Visual Surveillance,
IVC(22), No. 7, July 2004, pp. iii.
Elsevier DOI
0405
BibRef
Regazzoni, C.S.,
Foresti, G.L.,
Guest Editorial: Video Processing and Communications in Real-Time
Surveillance Systems,
RealTimeImg(7), No. 5, October 2001, pp. 381-388.
DOI Link
0110
BibRef
Collins, R.T.[Robert T.],
Lipton, A.J.[Alan J.],
Kanade, T.[Takeo],
Introduction to the Special Section on Video Surveillance,
PAMI(22), No. 8, August 2000, pp. 745-746.
IEEE DOI
0010
BibRef
Kojima, A.[Atsuhiro],
Tamura, T.[Takeshi],
Fukunaga, K.[Kunio],
Natural Language Description of Human Activities from Video Images
Based on Concept Hierarchy of Actions,
IJCV(50), No. 2, November 2002, pp. 171-184.
DOI Link
0210
BibRef
And:
Textual description of human activities by tracking head and hand
motions,
ICPR02(II: 1073-1077).
IEEE DOI
0211
BibRef
Kojima, A.,
Izumi, M.,
Tamura, T.,
Fukunaga, K.,
Generating Natural Language Description of Human Behavior from Video
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ICPR00(Vol IV: 728-731).
IEEE DOI
0009
BibRef
Gong, S.G.[Shao-Gang],
Buxton, H.[Hilary],
Understanding visual behaviour, Special Issue Introduction,
IVC(20), No. 12, October 2002, pp. 825-826.
Elsevier DOI
0210
BibRef
Buxton, H.[Hilary],
Learning and understanding dynamic scene activity: a review,
IVC(21), No. 1, January 2003, pp. 125-136.
Elsevier DOI
0301
BibRef
Namuduri, K.R.[Kameswara Rao],
Ramaswamy, V.[Veeru],
Preface, Video Analysis,
PRL(25), No. 7, May 2004, pp. 753-754.
Elsevier DOI
0405
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Hu, W.,
Tan, T.N.,
Wang, L.,
Maybank, S.J.,
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SMC-C(34), No. 3, August 2004, pp. 334-352.
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0409
Survey, Surveillance.
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Syeda-Mahmood, T.F.[Tanveer F.],
Haritaoglu, I.[Ismail],
Huang, T.S.[Thomas S.],
CVIU special issue on event detection in video,
CVIU(96), No. 2, November 2004, pp. 97-99.
Elsevier DOI
0410
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Chen, H.,
Wang, F.Y.[Fei-Yue],
Zeng, D.,
Intelligence and security informatics for homeland security:
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0501
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Regazzoni, C.S.[Carlo S.],
Introduction to the special issue on video object processing for
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RealTimeImg(11), No. 3, June 2005, pp. 167-171.
Elsevier DOI
0508
BibRef
And:
Erratum:
RealTimeImg(11), No. 5-6, October-December 2005, pp. 474.
Elsevier DOI
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Velastin, S.A.[Sergio A.],
Editorial. Special section on intelligent distributed surveillance
systems,
VISP(152), No. 2, April 2005, pp. 191.
DOI Link
0510
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VISP(152), No. 2, April 2005, pp. 192-204.
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Francois, A.R.J.[Alexandre R.J.],
Nevatia, R.[Ram],
Hobbs, J.[Jerry],
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VERL:
An Ontology Framework for Representing and Annotating Video Events,
MultMedMag(12), No. 4, October-December 2005, pp. 76-86.
IEEE DOI First order logic like syntax for describing composite events. And
set of predicates describing temporal constraints.
An event is typically triggered by a change in state.
VERL is a companion to VEML. Model events as composable, reduce complex
events to simpler using sequencing, iteration, alternation.
BibRef
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Nevatia, R.[Ram],
Hobbs, J.[Jerry],
Bolles, R.C.[Robert C.],
An Ontology for Video Event Representation,
EventVideo04(119).
IEEE DOI
0502
BibRef
Town, C.[Christopher],
Ontological inference for image and video analysis,
MVA(17), No. 2, May 2006, pp. 94-115.
Springer DOI
0605
BibRef
Earlier:
Ontology-Driven Bayesian Networks for Dynamic Scene Understanding,
EventVideo04(116).
IEEE DOI
0502
BibRef
Davies, E.R.,
Velastin, S.A.[Sergio A.],
Special Issue on Vision for Crime Detection and Prevention,
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Elsevier DOI
0609
BibRef
Weißenberg, N.[Norbert],
Gartmann, R.[Rüdiger],
Voisard, A.[Agnès],
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Springer DOI
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Aware of situation to control PDA displays, etc.
BibRef
Fuentes, L.M.[Luis M.],
Velastin, S.A.[Sergio A.],
People tracking in surveillance applications,
IVC(24), No. 11, 1 November 2006, pp. 1165-1171.
Elsevier DOI
0610
BibRef
Earlier:
From tracking to advanced surveillance,
ICIP03(III: 121-124).
IEEE DOI
0312
CCTV Surveillance; Tracking; Automatic surveillance
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Velastin, S.A.[Sergio A.],
Foresti, G.L.[Gian Luca],
Trivedi, M.M.[Mohan M.],
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MVA(18), No. 3-4, August 2007, pp. 135-137.
Springer DOI
0706
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Guerra-Filho, G.,
Aloimonos, Y.,
A Language for Human Action,
Computer(40), No. 5, May 2007, pp. 42-51.
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Rincon, M.,
Bachiller, M.,
Mira, J.,
On the correspondence between objects and events for the diagnosis of
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Elsevier DOI
0804
Visual surveillance systems; Image understanding; Description levels;
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Zhou, S.H.K.[Shao-Hua Kevin],
Recognition of Humans and Their Activities Using Video,
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Jones, G.A.[Graeme A.],
Special issue on Intelligent Visual Surveillance,
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Elsevier DOI
0711
BibRef
Ahmad, I.,
He, Z.,
Liao, M.,
Pereira, F.,
Sun, M.T.,
Special Issue on Video Surveillance,
CirSysVideo(18), No. 8, August 2008, pp. 1001-1005.
IEEE DOI
0809
BibRef
Dee, H.M.[Hannah M.],
Velastin, S.A.[Sergio A.],
How close are we to solving the problem of automated visual
surveillance?: A review of real-world surveillance, scientific progress
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MVA(19), No. 5-6, October 2008, pp. xx-yy.
Springer DOI
0810
BibRef
Tao, H.[Hai],
Sawhney, H.S.[Harpreet Singh],
Special issue on video surveillance research in industry and academia,
MVA(19), No. 5-6, October 2008, pp. xx-yy.
Springer DOI
0810
BibRef
Haering, N.C.[Niels C.],
Venetianer, P.L.[Péter L.],
Lipton, A.J.[Alan J.],
The evolution of video surveillance: an overview,
MVA(19), No. 5-6, October 2008, pp. xx-yy.
Springer DOI
0810
BibRef
Chang, S.F.,
Luo, J.,
Maybank, S.J.,
Schonfeld, D.,
Xu, D.,
An Introduction to the Special Issue on Event Analysis in Videos,
CirSysVideo(18), No. 11, November 2008, pp. 1469-1472.
IEEE DOI
0811
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Turaga, P.K.,
Chellappa, R.,
Subrahmanian, V.S.,
Udrea, O.,
Machine Recognition of Human Activities: A Survey,
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0811
Survey, Activity Recognition.
BibRef
Baumann, A.[Axel],
Boltz, M.[Marco],
Ebling, J.[Julia],
Koenig, M.[Matthias],
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Niem, W.[Wolfgang],
Warzelhan, J.K.[Jan Karl],
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A Review and Comparison of Measures for Automatic Video Surveillance
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JIVP(2008), No. 2008, pp. xx-yy.
DOI Link
0811
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Lavee, G.[Gal],
Rivlin, E.[Ehud],
Rudzsky, M.[Michael],
Understanding Video Events: A Survey of Methods for Automatic
Interpretation of Semantic Occurrences in Video,
SMC-C(39), No. 5, September 2009, pp. 489-504.
IEEE DOI
0909
BibRef
Lavee, G.[Gal],
Rudzsky, M.[Michael],
Rivlin, E.[Ehud],
Borzin, A.[Artyom],
Video Event Modeling and Recognition in Generalized Stochastic Petri
Nets,
CirSysVideo(20), No. 1, January 2010, pp. 102-118.
IEEE DOI
1002
BibRef
Earlier: A1, A4, A3, A2:
Building Petri Nets from Video Event Ontologies,
ISVC07(I: 442-451).
Springer DOI
0711
BibRef
Lavee, G.[Gal],
Rudzsky, M.[Michael],
Rivlin, E.[Ehud],
Propagating Certainty in Petri Nets for Activity Recognition,
CirSysVideo(23), No. 2, February 2013, pp. 326-337.
IEEE DOI
1301
BibRef
Earlier:
Propagating Uncertainty in Petri Nets for Activity Recognition,
ISVC10(II: 706-715).
Springer DOI
1011
BibRef
Hamid, R.[Raffay],
Maddi, S.[Siddhartha],
Johnson, A.[Amos],
Bobick, A.F.[Aaron F.],
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Isbell, C.[Charles],
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activities,
AI(173), No. 14, September 2009, pp. 1221-1244.
Elsevier DOI
0910
Temporal reasoning; Scene analysis; Computer vision
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Hamid, R.[Raffay],
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Bobick, A.F.[Aaron F.],
Target Tracking Using Residual Vector Quantization,
DICTA12(1-8).
IEEE DOI
1303
BibRef
Earlier:
Robust Surveillance on Compressed Video:
Uniform Performance from High to Low Bitrates,
AVSBS09(256-261).
IEEE DOI
0909
BibRef
Govea, V.[Vasquez],
Dizan, A.[Alejandro],
Incremental Learning for Motion Prediction of Pedestrians and Vehicles,
Springer2010, ISBN: 978-3-642-13641-2
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Buy this book: Incremental Learning for Motion Prediction of Pedestrians and Vehicles (Springer Tracts in Advanced Robotics)
1007
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Räty, T.D.,
Survey on Contemporary Remote Surveillance Systems for Public Safety,
SMC-C(40), No. 5, September 2010, pp. 493-515.
IEEE DOI
1008
Survey, Surveillance. State of the art.
BibRef
Chellappa, R.,
Heinzelman, W.,
Konrad, J.,
Schonfeld, D.,
Wolf, M.,
Special Section on Distributed Camera Networks:
Sensing, Processing, Communication, and Implementation,
IP(19), No. 10, October 2010, pp. 2513-2515.
IEEE DOI
1003
BibRef
Schneiderman, R.,
Trends In Video Surveillance Give DSP an Apps Boost,
SPMag(27), No. 6, 2010, pp. 6-12.
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1011
Special Reports.
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Chen, L.M.[Li-Ming],
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1011
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Zhang, J.,
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Buy this book: Intelligent Video Event Analysis and Understanding (Studies in Computational Intelligence)
1102
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di Stefano, L.[Luigi],
Regazzoni, C.S.[Carlo S.],
Schonfeld, D.[Dan],
Advanced Video-Based Surveillance,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link
1104
BibRef
Agaian, S.,
Tang, J.,
Jassim, S.,
Chen, C.L.P.,
Zhang, C.,
Cao, Y.,
Guest Editorial Introduction to the Special Issue on Pattern
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1109
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Weinland, D.[Daniel],
Ronfard, R.[Remi],
Boyer, E.[Edmond],
A Survey of Vision-Based Methods for Action Representation,
Segmentation and Recognition,
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Elsevier DOI
1102
Survey, Activity Recognition.
Award, CVIU, Most Cited. (2010-2012)
Action/activity recognition; Survey; Computer vision
BibRef
Gonzàlez, J.[Jordi],
Moeslund, T.B.[Thomas B.],
Wang, L.[Liang],
Semantic Understanding of Human Behaviors in Image Sequences:
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IVC(30), No. 3, March 2012, pp. 251-261.
Elsevier DOI
1204
BibRef
Earlier:
FG11(103-110).
IEEE DOI
1103
Dataset, Activity Recognition. Human motion database; Quantitative evaluation; Parametric and
cognitive sampling; Motion synthesis and analysis
BibRef
Aggarwal, J.K.,
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IVC(30), No. 8, August 2012, pp. 465-466.
Elsevier DOI
1209
Opinion paper; Motion understanding; Human activity recognition
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Human Action Recognition in Large-Scale Datasets Using Histogram of
Spatiotemporal Gradients,
AVSS12(106-111).
IEEE DOI
1211
BibRef
Lu, G.L.[Guo-Liang],
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PRL(34), No. 15, 2013, pp. 1936-1944.
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1309
Action segmentation
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PRL(34), No. 1, 1 January 2013, pp. 3-19.
Elsevier DOI
1211
Multi-camera video surveillance; Multi-camera calibration; Topology of
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Multi-camera activity analysis
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Chaquet, J.M.[Jose M.],
Carmona, E.J.[Enrique J.],
Fernandez-Caballero, A.[Antonio],
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CVIU(117), No. 6, June 2013, pp. 633-659.
Elsevier DOI
1304
Survey, Activity Recognition.
Dataset, Activity Recognition. Human action recognition; Human activity recognition; Database;
Dataset; Review; Survey
BibRef
Porikli, F.M.,
Bremond, F.,
Dockstader, S.L.,
Ferryman, J.M.,
Hoogs, A.,
Lovell, B.C.,
Pankanti, S.,
Rinner, B.,
Tu, P.,
Venetianer, P.L.,
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SPMag(30), No. 3, 2012, pp. 190-198.
IEEE DOI
1304
Survey, Surveillance. DSP Forum.
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Chen, L.[Lulu],
Wei, H.[Hong],
Ferryman, J.M.[James M.],
A survey of human motion analysis using depth imagery,
PRL(34), No. 15, 2013, pp. 1995-2006.
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Range data
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Geiger, A.,
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Urtasun, R.,
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Chavarriaga, R.[Ricardo],
Sagha, H.[Hesam],
Calatroni, A.[Alberto],
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PRL(34), No. 15, 2013, pp. 2033-2042.
Elsevier DOI
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Dataset, Activity Recognition. Activity recognition
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Kanade, T.[Takeo],
Keynote lecture 1: 'Video analysis of human body',
AVSS14(XIV-XIV)
IEEE DOI
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Keynote, overview of issues.
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Moon, Y.J.[Young-Jun],
Keynote lecture 3: 'Intelligent transport systems (ITS) for next
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AVSS14(XVI-XVI)
IEEE DOI
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Artificial intelligence
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Zhang, S.P.[Sheng-Ping],
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Signal, image and video processing special issue: Semantic
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Wu, J.Z.[Jian-Zhai],
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1411
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Tian, Y.H.[Yong-Hong],
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IEEE_Int_Sys(29), No. 5, September 2014, pp. 30-39.
IEEE DOI
1402
BibRef
Earlier: A5, A3, A2, A1, Only:
Overview of the IEEE 1857 surveillance groups,
ICIP13(1505-1509)
IEEE DOI
1402
IEEE 1857
See also Optimizing the Hierarchical Prediction and Coding in HEVC for Surveillance and Conference Videos With Background Modeling.
BibRef
Wang, L.[Liang],
Patras, I.[Ioannis],
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Mori, G.[Greg],
Davis, L.S.[Larry S.],
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Elsevier DOI
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Fleet, D.[David],
Shotton, J.[Jamie],
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Springer DOI
1606
BibRef
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Xu, R.[Ran],
Yu, H.N.[Hao-Nan],
Siskind, J.M.[Jeffrey Mark],
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MVA(27), No. 7, October 2016, pp. 983-995.
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1610
Dataset, Actions. LCA Dataset.
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Hadfield, S.[Simon],
Lebeda, K.[Karel],
Bowden, R.[Richard],
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Springer DOI
1702
BibRef
Earlier: A1, A3, Only:
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CVPR13(3398-3405)
IEEE DOI
1309
Dataset, Attion Recognition. Hollywood3D dataset.
3.5d
BibRef
Lebeda, K.[Karel],
Hadfield, S.[Simon],
Bowden, R.[Richard],
TMAGIC: A Model-Free 3D Tracker,
IP(26), No. 9, September 2017, pp. 4378-4388.
IEEE DOI
1708
image motion analysis, image reconstruction, image sequences,
object tracking, 2D trackers, 3D motion modelling, TMAGIC,
model-free 3D tracker, object properties, online leader-board,
out-of-plane motion, structure from motion, visual tracking,
Cameras, Feature extraction, Solid modeling,
Tracking,
Visualization, 3D tracking, Gaussian process, Machine vision, SLAM,
image motion, structure from motion, visual, tracking
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Idrees, H.[Haroon],
Zamir, A.R.[Amir R.],
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Elsevier DOI
1702
Action recognition
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Xian, Y.[Yang],
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CirSysVideo(27), No. 3, March 2017, pp. 624-634.
IEEE DOI
1703
Encoding
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Tan, T.,
Maybank, S.J.[Stephen J.],
Chellappa, R.,
Aggarval, J.,
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1704
Algorithm design and analysis
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Zhang, Q.,
Sun, H.,
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Edge Video Analytics for Public Safety: A Review,
PIEEE(107), No. 8, August 2019, pp. 1675-1696.
IEEE DOI
1908
Safety, Cameras, Law enforcement, Video surveillance,
Streaming media, Image edge detection, Robot vision systems,
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Andonian, A.[Alex],
Zhou, B.L.[Bo-Lei],
Ramakrishnan, K.[Kandan],
Bargal, S.A.[Sarah Adel],
Yan, T.[Tom],
Brown, L.[Lisa],
Fan, Q.F.[Quan-Fu],
Gutfreund, D.[Dan],
Vondrick, C.[Carl],
Oliva, A.[Aude],
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PAMI(42), No. 2, February 2020, pp. 502-508.
IEEE DOI
2001
WWW Link.
Dataset, Action. Videos, Visualization, Feature extraction, Vocabulary, Animals,
Convolution, Video dataset, event recognition
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Hussain, A.J.[Abir Jaafar],
Khan, W.[Wasiq],
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Al-Shabandar, R.[Raghad],
Al-Jumeily, D.[Dhiya],
Liatsis, P.[Panos],
Lossy and Lossless Video Frame Compression:
A Novel Approach for High-Temporal Video Data Analytics,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link
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Elharrouss, O.[Omar],
Almaadeed, N.[Noor],
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JVCIR(77), 2021, pp. 103116.
Elsevier DOI
2106
Video surveillance system, Video analysis, Video surveillance systems trends
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Pal, R.[Ratnabali],
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Dogra, D.P.[Debi Prosad],
Kar, S.[Samarjit],
Roy, P.P.[Partha Pratim],
Prasad, D.K.[Dilip K.],
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Surveys(54), No. 6, July 2021, pp. xx-yy.
DOI Link
2108
unsupervised learning, topic model, Video analysis
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Damen, D.[Dima],
Doughty, H.[Hazel],
Farinella, G.M.[Giovanni Maria],
Fidler, S.[Sanja],
Furnari, A.[Antonino],
Kazakos, E.[Evangelos],
Moltisanti, D.[Davide],
Munro, J.[Jonathan],
Perrett, T.[Toby],
Price, W.[Will],
Wray, M.[Michael],
The EPIC-KITCHENS Dataset: Collection, Challenges and Baselines,
PAMI(43), No. 11, November 2021, pp. 4125-4141.
IEEE DOI
2110
Annotations, Cameras, Benchmark testing, Task analysis,
Streaming media, YouTube, Indexes, Egocentric vision,
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See also EPIC-KITCHENS.
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Zhao, Y.Y.[Ying-Ying],
Dong, M.Z.[Ming-Zhi],
Wang, Y.J.[Yu-Jiang],
Feng, D.[Da],
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Dick, R.P.[Robert P.],
Li, D.S.[Dong-Sheng],
Lu, T.[Tun],
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Shang, L.[Li],
A Reinforcement-Learning-Based Energy-Efficient Framework for
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MultMed(24), No. 2022, pp. 2150-2163.
IEEE DOI
2204
Task analysis, Visual analytics, Energy resolution,
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Surveys(55), No. 2, February 2023, pp. xx-yy.
DOI Link
2212
Unobtrusive sensing, signal processing, IoT, data processing, HiTL
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Liao, Y.[Yiyi],
Xie, J.[Jun],
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KITTI-360: A Novel Dataset and Benchmarks for Urban Scene
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Semantics, Annotations, Task analysis, Benchmark testing, Cameras,
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Kristan, M.[Matej],
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Bernardino, A.[Alexandre],
Dawkins, M.[Matthew],
Raitoharju, J.[Jenni],
Quan, Y.T.[Yi-Tong],
Atmaca, A.[Adem],
Höfer, T.[Timon],
Zhang, Q.M.[Qi-Ming],
Xu, Y.F.[Yu-Fei],
Zhang, J.[Jing],
Tao, D.C.[Da-Cheng],
Sommer, L.[Lars],
Spraul, R.[Raphael],
Zhao, H.[Hangyue],
Zhang, H.[Hongpu],
Zhao, Y.[Yanyun],
Augustin, J.L.[Jan Lukas],
Jeon, E.I.[Eui-Ik],
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Breckon, T.P.[Toby P.],
Kundargi, S.[Shivanand],
Anvekar, T.[Tejas],
Tabib, R.A.[Ramesh Ashok],
Mudengudi, U.[Uma],
Vats, A.[Arpita],
Song, Y.[Yang],
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1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge
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Maritime23(265-302)
IEEE DOI
2302
Training, Conferences, Object detection, Detectors,
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VDU22(4907-4916)
IEEE DOI
2210
No authors listed.
Pattern recognition
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Tsanousa, A.[Athina],
Mavropoulos, T.[Thanassis],
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2203
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Activity22(143-150)
IEEE DOI
2202
Deep Intermodal Video Analytics (DIVA) program has sponsored the
development of systems that detect and recognize activities in
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Software, Security, Software engineering
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Le, H.,
Smailis, C.,
Shi, L.,
Kakadiaris, I.,
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IEEE DOI
2006
Cameras, Image edge detection, Face detection, Face recognition,
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Avgerinakis, K.,
Karakostas, A.,
Vrochidis, S.,
Kompatsiaris, I.,
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IVMSP18(1-5)
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Electromagnetic compatibility, Flickr, Image segmentation,
Estimation, Safety, Machine learning, deep learning,
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BEST16(III: 393-407).
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1704
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Mei, L.[Lin],
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Wang, J.[Jian],
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AVSS17(1-6)
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1806
public administration, video signal processing,
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BEST16(III: 441-452).
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1704
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Mann, S.,
Surveillance (Oversight), Sousveillance (Undersight), and
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MoveSurveillance16(1408-1417)
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Nawaz, T.,
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Ferryman, J.,
PETS 2017: Dataset and Challenge,
PETS17(2126-2132)
IEEE DOI
1709
Boats, Cameras, Measurement, Mobile communication,
Surveillance, Visualization
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Patino, L.,
Cane, T.,
Vallee, A.,
Ferryman, J.,
PETS 2016: Dataset and Challenge,
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IEEE DOI
1612
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AVSS14(355-360)
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1411
Dataset, Surveillance. Cameras
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Aved, A.,
Seetharaman, G.,
Video-based activity analysis using the L1 tracker on VIRAT data,
AIPR13(1-8)
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ActionSim13(245-250)
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Dataset,Surveillance.
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Industrial paper. What can really be done, focus on doable systems.
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1109
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0909
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1208
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Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Surveillance Systems, Privacy Protection, Issues, Techniques, Face Obscuration .