LHI Surveillance Dataset,
Annotated surveillance images.
Online2008
HTML Version.
Dataset, Segmentation.
Subset of larger dataset.
See also Lotus Hill Institute.
BibRef
0800
CLEAR: Classification of Events, Activities and Relationships,
MTPH07
WWW Version.
Dataset, Activity Recogniton.
BibRef
0700
i-LIDS: Bag and vehicle detection challenge,
Online2007
BibRef
0700
AVSBS07
HTML Version.
Dataset, Activity Recogniton. Data used at Advanced Video and Signal Based Surveillance, 2007.
BibRef
PETS 2006 Benchmark Data,
Online2006
BibRef
0600
PETS06
HTML Version.
Dataset, Activity Recogniton. Data used at International Workshop on
Performance Evaluation of Tracking and Surveillance
2006.
BibRef
PETS 2001 Benchmark Data,
Online2001
BibRef
0100
PETS01
WWW Version.
Dataset, Activity Recogniton. Data used at International Workshop on
Performance Evaluation of Tracking and Surveillance 2001.
BibRef
OTCBVS Benchmark Dataset Collection,
OTCBVS072007
WWW Version.
Dataset, Activity Recogniton. Beyound the Visual Spectrum (IR especially).
Data for various OTCBVS workshops.
BibRef
0700
Boyd, J.E.[Jeffrey E.],
Meloche, J.[Jean],
Evaluation of statistical and multiple-hypothesis tracking for video
traffic surveillance,
MVA(13), No. 5-6, 2003, pp. 344-351.
HTML Version.
0304
BibRef
Boyd, J.E.,
Meloche, J.,
Vardi, Y.,
Statistical Tracking in Video Traffic Surveillance,
ICCV99(163-168).
IEEE DOI Link
BibRef
9900
Oberti, F.[Franco],
Stringa, E.[Elena],
Vernazza, G.[Gianni],
Performance Evaluation Criterion for Characterizing Video-Surveillance
Systems,
RealTimeImg(7), No. 5, October 2001, pp. 457-471.
WWW Version.
0110
BibRef
Oberti, F.[Franco],
Teschioni, A.[Andrea],
Regazzoni, C.S.[Carlo S.],
ROC Curves for Performance Evaluation of Video Sequences Processing
Systems for Surveillance Applications,
ICIP99(II:949-953).
IEEE Abstract.
BibRef
9900
Fisher, R.B.[Robert B.],
CAVIAR Test Case Scenarios,
Online BookOctober 2004.
WWW Version.
Dataset, Video. From the EC funded CAVIAR project
(Context Aware Vision using Image-based Active Recognition).
The sequences are labelled (in XML) with both the tracked persons and
a semantic description of their activities.
81 video sequences comprising about 90K frames.
These sequences include indoor plaza and shopping center
observations of individuals and small groups of people walking, browsing,
window shopping, fighting, meeting, leaving packages behind, collapsing,
entering and exiting shops, etc.
BibRef
0410
Optic Flow Data,
Edinburgh2007.
Smoothed flow sequences for the Waverly train station scene.
WWW Version.
Dataset, Video. Behavior, pedestrian analysis.
BibRef
0700
BEHAVE Interactions Test Case Scenarios,
Edinburgh2007.
Two views of various scenarios of people acting out various interactions.
WWW Version.
Dataset, Video. Behavior, pedestrian analysis.
Includes ground truth bounding boxes for much of the data.
BibRef
0700
Sigal, L.[Leonid],
Balan, A.O.[Alexandru O.],
Black, M.J.[Michael J.],
HumanEva: Synchronized Video and Motion Capture Dataset and Baseline
Algorithm for Evaluation of Articulated Human Motion,
IJCV(87), No. 1-2, March 2010, pp. xx-yy.
Springer DOI Link
1001
Dataset, Human Motion.
BibRef
Earlier: A1, A3, Only:
HumanEva: Synchronized Video and Motion Capture Dataset for Evaluation of Articulated Human Motion,
BrownTechnical Report CS-06-08, September 2006.
HTML Version. For the dataset:
HTML Version. Calibrated video sequences synchronized with motion capture data.
BibRef
Sanderson, C.[Conrad],
Bigdeli, A.[Abbas],
Shan, T.[Ting],
Chen, S.K.[Shao-Kang],
Berglund, E.[Erik],
Lovell, B.C.[Brian C.],
Intelligent CCTV for Mass Transport Security:
Challenges and Opportunities for Video and Face Processing,
ELCVIA(6), No. 3, December 2007, pp. 30-41.
WWW Version.
0801
See also Experimental Analysis of Face Recognition on Still and CCTV Images.
BibRef
Norouznezhad, E.,
Bigdeli, A.,
Postula, A.,
Lovell, B.C.,
A high resolution smart camera with GigE Vision extension for
surveillance applications,
ICDSC08(1-8).
IEEE DOI Link
0809
BibRef
Lazarevic-McManus, N.,
Renno, J.R.,
Makris, D.,
Jones, G.A.,
An object-based comparative methodology for motion detection based on
the F-Measure,
CVIU(111), No. 1, July 2008, pp. 74-85.
WWW Version.
0711
BibRef
Earlier: A1, A2, A4, Only:
Performance evaluation in visual surveillance using the F-measure,
VSSN06(45-52).
WWW Version.
0701
Visual surveillance; Motion detection; Performance evaluation;
ROC analysis; F-Measure
BibRef
Altun, K.[Kerem],
Barshan, B.[Billur],
Tuncel, O.[Orkun],
Comparative study on classifying human activities with miniature
inertial and magnetic sensors,
PR(43), No. 10, October 2010, pp. 3605-3620.
Elsevier DOI Link
WWW Version.
1007
Inertial sensors; Gyroscope; Accelerometer; Magnetometer; Activity
recognition and classification; Feature extraction; Feature reduction;
Bayesian decision making; Rule-based algorithm; Decision tree;
Least-squares method; k-Nearest neighbor; Dynamic time warping;
Support vector machines; Artificial neural networks
BibRef
Venetianer, P.L.[Peter L.],
Deng, H.L.[Hong-Li],
Performance evaluation of an intelligent video surveillance system:
A case study,
CVIU(114), No. 11, November 2010, pp. 1292-1302.
Elsevier DOI Link
WWW Version.
1011
Performance evaluation; Intelligent video surveillance; Embedded vision
BibRef
Sasse, M.A.[M. Angela],
Not Seeing the Crime for the Cameras?,
CACM(53), No. 2, February 2010, pp. 22-25.
WWW Version.
1101
Why it is difficult - but essential - to monitor the effectiveness of
security technologies.
BibRef
Fernández Llorca, D.[David],
Parra, I.[Ignacio],
Sotelo, M.Á.[Miguel Ángel], and
Lacey, G.[Gerard],
A vision-based system for automatic hand washing quality assessment,
MVA(22), No. 2, March 2011, pp. 219-234.
WWW Version.
1103
BibRef
Fernández Llorca, D.[David],
Vilarino, F.,
Zhou, J.,
Lacey, G.,
A multi-class SVM classifier for automatic hand washing quality
assessment,
BMVC07(xx-yy).
PDF Version.
0709
BibRef
Zhou, J.[Jiang],
Vilarino, F.[Fernando],
Lacey, G.[Gerard],
Li, X.C.[Xu-Chun],
Statistical analysis of ground truth in human labeled data,
IMVIP07(211-211).
IEEE DOI Link
0709
Analysis of human analysis of hand washing videos.
BibRef
Israel, S.A.[Steven A.],
Evaluation of ISR technologies for counter insurgency warfare,
AIPR10(1-5).
IEEE DOI Link
1010
BibRef
Ryoo, M.S.,
Chen, C.C.[Chia-Chih],
Aggarwal, J.K.,
Roy-Chowdhury, A.[Amit],
An Overview of Contest on Semantic Description of Human Activities
(SDHA) 2010,
ICPR-Contests10(270-285).
Springer DOI Link
1008
BibRef
Singh, S.,
Velastin, S.A.,
Ragheb, H.,
MuHAVi: A Multicamera Human Action Video Dataset for the Evaluation of
Action Recognition Methods,
AVSS10(48-55).
IEEE DOI Link
1009
BibRef
Desurmont, X.,
Carincotte, C.,
Bremond, F.,
Intelligent Video Systems: A Review of Performance Evaluation Metrics
that Use Mapping Procedures,
AVSS10(127-134).
IEEE DOI Link
1009
BibRef
Kuhn, W.[Werner],
A Functional Ontology of Observation and Measurement,
GS09(26-43).
Springer DOI Link
0912
BibRef
Rose, T.[Travis],
Fiscus, J.[Jonathan],
Over, P.[Paul],
Garofolo, J.[John],
Michel, M.[Martial],
The TRECVid 2008 Event Detection evaluation,
WACV09(1-8).
IEEE DOI Link
0912
BibRef
Ferryman, J.M.,
Ellis, A.,
PETS2010: Dataset and Challenge,
AVSS10(143-150).
IEEE DOI Link
1009
BibRef
Ellis, A.,
Ferryman, J.M.,
PETS2010 and PETS2009 Evaluation of Results Using Individual Ground
Truthed Single Views,
AVSS10(135-142).
IEEE DOI Link
1009
BibRef
Ellis, A.,
Shahrokni, A.,
Ferryman, J.M.,
PETS2009 and Winter-PETS 2009 results: A combined evaluation,
PETS-Winter09(1-8).
IEEE DOI Link
0912
BibRef
Ferryman, J.M.,
Shahrokni, A.,
PETS2009: Dataset and challenge,
PETS-Winter09(1-6).
IEEE DOI Link
0912
BibRef
Kovesi, P.[Peter],
Video Surveillance: Legally Blind?,
DICTA09(204-211).
IEEE DOI Link
0912
Surveillance cameras are not very good.
BibRef
Wang, H.[Heng],
Ullah, M.M.[Muhammad Muneeb],
Klaser, A.[Alexander],
Laptev, I.[Ivan],
Schmid, C.[Cordelia],
Evaluation of local spatio-temporal features for action recognition,
BMVC09(xx-yy).
PDF Version.
0909
BibRef
Sulman, N.[Noah],
Sanocki, T.A.[Thomas A.],
Goldgof, D.[Dmitry],
Kasturi, R.[Rangachar],
How effective is human video surveillance performance?,
ICPR08(1-3).
IEEE DOI Link
0812
BibRef
Vezzani, R.[Roberto],
Cucchiara, R.[Rita],
Annotation Collection and Online Performance Evaluation for Video
Surveillance: The ViSOR Project,
AVSBS08(227-234).
IEEE DOI Link
0809
BibRef
Roth, D.,
Koller-Meier, E.,
Rowe, D.,
Moeslund, T.B.,
Van Gool, L.J.,
Event-Based Tracking Evaluation Metric,
Motion08(1-8).
IEEE DOI Link
0801
BibRef
Nghiem, A.T.,
Bremond, F.,
Thonnat, M.,
Valentin, V.,
ETISEO, performance evaluation for video surveillance systems,
AVSBS07(476-481).
IEEE DOI Link
0709
BibRef
Garofolo, J.[John],
Directions in automatic video analysis evaluations at NIST,
AVSBS07(6-6).
IEEE DOI Link
0709
Evaluation, Video Analysis.
BibRef
Taylor, G.R.[Geoffrey R.],
Chosak, A.J.[Andrew J.],
Brewer, P.C.[Paul C.],
OVVV: Using Virtual Worlds to Design and Evaluate Surveillance Systems,
VS07(1-8).
IEEE DOI Link
0706
BibRef
Negre, A.,
Tran, H.,
Gourier, N.,
Hall, D.,
Lux, A.,
Crowley, J.L.,
Comparative Study of People Detection in Surveillance Scenes,
SSPR06(100-108).
Springer DOI Link
0608
BibRef
Nghiem, A.T.,
Bremond, F.,
Thonnat, M.,
Ma, R.,
A New Evaluation Approach for Video Processing Algorithms,
Motion07(15-15).
IEEE DOI Link
0702
To avoid dataset dependence.
The maximum difficulty level of the videos at which the algorithm is
performing good enough is defined as the upper bound of the algorithm
capacity for handling the problem.
BibRef
Tsuchiya, M.[Masamitsu],
Fujiyoshi, H.[Hironobu],
Evaluating Feature Importance for Object Classification in Visual
Surveillance,
ICPR06(II: 978-981).
IEEE DOI Link
0609
BibRef
Lienhart, R.[Rainer],
Algorithm competition,
VSSN05(53-54).
WWW Version.
0511
Evaluation discussion. For surveillance applications.
BibRef
List, T.,
Bins, J.,
Vazquez, J.,
Fisher, R.B.,
Performance evaluating the evaluator,
PETS05(129-136).
IEEE DOI Link
0602
How to compare to human results.
BibRef
Annesley, J.,
Orwell, J.,
Renno, J.R.,
Evaluation of MPEG7 color descriptors for visual surveillance retrieval,
PETS05(105-112).
IEEE DOI Link
0602
BibRef
Muller-Schneiders, S.,
Jager, T.,
Loos, H.S.,
Niem, W.,
Performance evaluation of a real time video surveillance system,
PETS05(137-143).
IEEE DOI Link
0602
BibRef
Ziliani, F.,
Velastin, S.A.,
Porikli, F.M.,
Marcenaro, L.,
Kelliher, T.,
Cavallaro, A.,
Bruneaut, P.,
Performance Evaluation of Event Detection Solutions:
The CREDS Experience,
AVSBS05(201-206).
IEEE DOI Link
0602
BibRef
Zang, Q.[Qi],
Klette, R.[Reinhard],
Object Classification and Tracking in Video Surveillance,
CAIP03(198-205).
WWW Version.
0311
BibRef
Zang, Q.[Qi],
Klette, R.[Reinhard],
Evaluation of an Adaptive Composite Gaussian Model in Video
Surveillance,
CAIP03(165-172).
WWW Version.
0311
BibRef
Jaynes, C.,
Webb, S.,
Steele, R.M.,
Xiong, Q.,
An Open Development Environment for Evaluation of Video Surveillance
Systems,
PETS02(32-39).
0207
BibRef
Ferryman, J.M.,
Performance Evaluation of Tracking and Surveillance,
EEMCV01(xx-yy).
0110
BibRef
Ellis, T.,
Performance Metrics and Methods for Tracking in Surveillance,
PETS02(26-31).
0207
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Vehicle Motion Understanding and Analysis .