LHI Surveillance Dataset,
Annotated surveillance images.
Online2008
HTML Version.
Dataset, Segmentation.
Subset of larger dataset.
See also Lotus Hill Institute.
BibRef
0800
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).
WWW Version.
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. IEEE Top Reference.
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., and
Black, M.J.,
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.
Dataset, Human Motion. Calibrated video sequences synchronized with motion capture data.
BibRef
0609
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
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.
0701Visual surveillance; Motion detection; Performance evaluation;
ROC analysis; F-Measure
BibRef
Garofolo, J.[John],
Directions in automatic video analysis evaluations at NIST,
AVSBS07(6-6).
WWW Version.
0709
Evaluation, Video Analysis.
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).
WWW Version.
0709Analysis of human analysis of hand washing videos.
BibRef
Llorca, D.F.,
Vilarino, F.,
Zhou, J.,
Lacey, G.,
A multi-class SVM classifier for automatic hand washing quality
assessment,
BMVC07(xx-yy).
PDF Version.
0709
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).
WWW Version.
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).
WWW Version.
0608
BibRef
Nghiem, A.T.,
Bremond, F.,
Thonnat, M.,
Ma, R.,
A New Evaluation Approach for Video Processing Algorithms,
Motion07(15-15).
WWW Version.
0702To 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
Spagnolo, P.,
Caroppo, A.,
Leo, M.,
Martiriggiano, T.,
d'Orazio, T.,
An Abandoned/Removed Objects Detection Algorithm and Its Evaluation on
PETS Datasets,
AVSBS06(17-17).
WWW Version.
0611
BibRef
Tsuchiya, M.[Masamitsu],
Fujiyoshi, H.[Hironobu],
Evaluating Feature Importance for Object Classification in Visual
Surveillance,
ICPR06(II: 978-981).
WWW Version.
0609
BibRef
Lienhart, R.[Rainer],
Algorithm competition,
VSSN05(53-54).
WWW Version.
0511Evaluation discussion. For surveillance applications.
BibRef
List, T.,
Bins, J.,
Vazquez, J.,
Fisher, R.B.,
Performance evaluating the evaluator,
PETS05(129-136).
WWW Version.
0602How to compare to human results.
BibRef
Annesley, J.,
Orwell, J.,
Renno, J.P.,
Evaluation of MPEG7 color descriptors for visual surveillance retrieval,
PETS05(105-112).
WWW Version.
0602
BibRef
Muller-Schneiders, S.,
Jager, T.,
Loos, H.S.,
Niem, W.,
Performance evaluation of a real time video surveillance system,
PETS05(137-143).
WWW Version.
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).
WWW Version.
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 .