Kim, C.[Changick],
Hwang, J.N.[Jenq-Neng],
Object-based video abstraction for video surveillance systems,
CirSysVideo(12), No. 12, December 2002, pp. 1128-1138.
IEEE Top Reference.
0301
BibRef
Earlier:
Object-based Video Abstraction Using Cluster Analysis,
ICIP01(II: 657-660).
IEEE DOI
0108
BibRef
Pritch, Y.[Yael],
Rav-Acha, A.[Alex],
Peleg, S.[Shmuel],
Nonchronological Video Synopsis and Indexing,
PAMI(30), No. 11, November 2008, pp. 1971-1984.
IEEE DOI
0809
BibRef
Earlier: A2, A1, A3:
Making a Long Video Short: Dynamic Video Synopsis,
CVPR06(I: 435-441).
IEEE DOI
0606
Partly mosaicing, partly change detection.
Capture video and generate a synopsis image that contains the constant
background plus some subset of the moving objects. E.g. Street scene plus the
pedestrians, or the same scene plus moving cars.
BibRef
Pritch, Y.[Yael],
Kav-Venaki, E.[Eitam],
Peleg, S.[Shmuel],
Shift-map image editing,
ICCV09(151-158).
IEEE DOI
0909
BibRef
Pritch, Y.[Yael],
Ratovitch, S.[Sarit],
Hendel, A.[Avishai],
Peleg, S.[Shmuel],
Clustered Synopsis of Surveillance Video,
AVSBS09(195-200).
IEEE DOI
0909
BibRef
Peleg, S.[Shmuel],
Keynote lecture 2: Video synopsis,
AVSS13(XVII-XVII)
IEEE DOI
1311
object recognition
BibRef
Xiang, T.[Tao],
Gong, S.G.[Shao-Gang],
Optimising dynamic graphical models for video content analysis,
CVIU(112), No. 3, December 2008, pp. 310-323.
Elsevier DOI
0811
Video content analysis; Structure scoring; Graphical models; Hidden
Markov models; Surveillance video segmentation; Group activity
modelling
See also Beyond Tracking: Modelling Activity and Understanding Behaviour.
BibRef
Alexiou, I.,
Xiang, T.[Tao],
Gong, S.G.[Shao-Gang],
Exploring synonyms as context in zero-shot action recognition,
ICIP16(4190-4194)
IEEE DOI
1610
BibRef
Earlier:
Learning a joint discriminative-generative model for action
recognition,
WSSIP15(1-4)
IEEE DOI
1603
Computational modeling.
gradient methods
BibRef
Mehmood, K.,
Mrak, M.[Marta],
Calic, J.[Janko],
Kondoz, A.M.[Ahmet M.],
Object tracking in surveillance videos using compressed domain features
from scalable bit-streams,
SP:IC(24), No. 10, November 2009, pp. 814-824.
Elsevier DOI
0911
Object tracking; Scalable video coding; Compressed domain analysis;
Motion vectors
BibRef
Höferlin, M.[Markus],
Höferlin, B.[Benjamin],
Heidemann, G.[Gunther],
Weiskopf, D.[Daniel],
Interactive Schematic Summaries for Faceted Exploration
of Surveillance Video,
MultMed(15), No. 4, 2013, pp. 908-920.
IEEE DOI
1307
BibRef
Earlier: A1, A2, A4, A3:
Interactive schematic summaries for exploration of surveillance video,
ICMR11(9).
DOI Link
1301
image motion analysis; video surveillance
BibRef
Wang, S.Z.[Shi-Zheng],
Wang, Z.Y.[Zhong-Yuan],
Hu, R.M.[Rui-Min],
Surveillance video synopsis in the compressed domain for fast video
browsing,
JVCIR(24), No. 8, 2013, pp. 1431-1442.
Elsevier DOI
1312
Surveillance video
BibRef
Chen, Y.[Ying],
Zhang, B.L.[Bai-Ling],
Surveillance video summarisation by jointly applying moving object
detection and tracking,
IJCVR(4), No. 3, 2014, pp. 212-234.
DOI Link
1407
BibRef
Huang, C.R.[Chun-Rong],
Chung, P.C.J.,
Yang, D.K.[Di-Kai],
Chen, H.C.[Hsing-Cheng],
Huang, G.J.[Guan-Jie],
Maximum a Posteriori Probability Estimation for Online Surveillance
Video Synopsis,
CirSysVideo(24), No. 8, August 2014, pp. 1417-1429.
IEEE DOI
1410
maximum likelihood estimation
BibRef
Cooharojananone, N.[Nagul],
Kasamwattanarote, S.[Siriwat],
Lipikorn, R.[Rajalida],
Satoh, S.[Shin'ichi],
Automated real-time video surveillance summarization framework,
RealTimeIP(10), No. 3, September 2015, pp. 513-532.
Springer DOI
1509
BibRef
Li, X.,
Wang, Z.,
Lu, X.,
Surveillance Video Synopsis via Scaling Down Objects,
IP(25), No. 2, February 2016, pp. 740-755.
IEEE DOI
1601
Image coding
BibRef
Li, X.,
Wang, Z.,
Lu, X.,
Video Synopsis in Complex Situations,
IP(27), No. 8, August 2018, pp. 3798-3812.
IEEE DOI
1806
greedy algorithms, image segmentation, object detection,
object tracking, optimisation, video signal processing,
surveillance video
BibRef
Wang, S.Z.[Shi-Zheng],
Yang, J.W.[Jian-Wei],
Zhao, Y.Y.[Yan-Yun],
Cai, A.N.[An-Ni],
Li, S.Z.[Stan Z.],
A surveillance video analysis and storage scheme for scalable synopsis
browsing,
VS11(1947-1954).
IEEE DOI
1201
BibRef
Cote, M.,
Jean, F.,
Albu, A.B.,
Capson, D.,
Video summarization for remote invigilation of online exams,
WACV16(1-9)
IEEE DOI
1606
Computational modeling
BibRef
Zhang, S.,
Zhu, Y.Y.,
Roy-Chowdhury, A.K.,
Context-Aware Surveillance Video Summarization,
IP(25), No. 11, November 2016, pp. 5469-5478.
IEEE DOI
1610
Automobiles
BibRef
Salehin, M.M.[M. Musfequs],
Paul, M.[Manoranjan],
Adaptive fusion of human visual sensitive features for surveillance
video summarization,
JOSA-A(34), No. 5, May 2017, pp. 814-826.
DOI Link
1705
Fibers, polarization-maintaining,
Lasers, distributed-feedback, Fiber, Bragg gratings
BibRef
Panda, R.,
Roy-Chowdhury, A.K.,
Multi-View Surveillance Video Summarization via Joint Embedding and
Sparse Optimization,
MultMed(19), No. 9, September 2017, pp. 2010-2021.
IEEE DOI
1708
Cameras, Correlation, Feature extraction, Linear programming,
Optimization, Sparse matrices, Surveillance, Camera network,
multi-view video, sparse optimization, video, summarization
BibRef
Tani, M.Y.K.[Mohammed Yassine Kazi],
Ghomari, A.[Abdelghani],
Lablack, A.[Adel],
Bilasco, I.M.[Ioan Marius],
OVIS: ontology video surveillance indexing and retrieval system,
MultInfoRetr(6), No. 4, December 2017, pp. 295-316.
Springer DOI
1712
BibRef
Gao, Z.[Zhen],
Lu, G.L.[Guo-Liang],
Yan, P.[Peng],
Wang, L.[Liang],
Retrospective analysis of time series for frame selection in
surveillance video summarization,
SIViP(11), No. 4, May 2017, pp. 581-588.
WWW Link.
1704
BibRef
Zhang, Y.,
Tao, R.,
Wang, Y.,
Motion-State-Adaptive Video Summarization via Spatiotemporal Analysis,
CirSysVideo(27), No. 6, June 2017, pp. 1340-1352.
IEEE DOI
1706
Color, Computational modeling, Feature extraction,
Motion segmentation, Semantics, Surveillance, Visualization,
Motion state adaptive, spatiotemporal analysis, video, summarization
BibRef
Xu, X.,
Hospedales, T.M.[Tim M.],
Gong, S.G.[Shao-Gang],
Discovery of Shared Semantic Spaces for Multiscene Video Query and
Summarization,
CirSysVideo(27), No. 6, June 2017, pp. 1353-1367.
IEEE DOI
1706
Cameras, Computational modeling, Hidden Markov models, Layout,
Redundancy, Semantics, Surveillance, Scene understanding,
transfer learning, video summarization, visual, surveillance
BibRef
Wang, M.[Miao],
Liang, J.B.[Jun-Bang],
Zhang, S.H.[Song-Hai],
Lu, S.P.[Shao-Ping],
Shamir, A.[Ariel],
Hu, S.M.[Shi-Min],
Hyper-Lapse From Multiple Spatially-Overlapping Videos,
IP(27), No. 4, April 2018, pp. 1735-1747.
IEEE DOI
1802
Time lapse, except when something is happening.
Cameras, Navigation, Optimization,
Trajectory, Videos, Visualization, Hyper-lapse video, time-lapse,
video synthesis
BibRef
Gao, Z.[Zhen],
Lu, G.L.[Guo-Liang],
Lyu, C.[Chen],
Yan, P.[Peng],
Key-frame selection for automatic summarization of surveillance videos:
a method of multiple change-point detection,
MVA(29), No. 7, October 2018, pp. 1101-1117.
WWW Link.
1810
BibRef
Thomas, S.S.,
Gupta, S.,
Subramanian, V.K.,
Event Detection on Roads Using Perceptual Video Summarization,
ITS(19), No. 9, September 2018, pp. 2944-2954.
IEEE DOI
1809
Roads, Surveillance, Cameras, Road accidents, Cost function,
Accident detection, optimization framework,
surveillance
BibRef
Baskurt, K.B.[Kemal Batuhan],
Samet, R.[Refik],
Video synopsis: A survey,
CVIU(181), 2019, pp. 26-38.
Elsevier DOI
1903
Survey, Video Synopsis. Video surveillance, Video processing, Video synopsis,
Motion detection, Object tracking, Optimization,
Stitching
BibRef
Zhang, Z.,
Nie, Y.,
Sun, H.,
Zhang, Q.,
Lai, Q.,
Li, G.,
Xiao, M.,
Multi-View Video Synopsis via Simultaneous Object-Shifting and
View-Switching Optimization,
IP(29), No. 1, 2020, pp. 971-985.
IEEE DOI
1910
Surveillance, Cameras, Switches, Redundancy, Optimization,
Electron tubes, Dynamic programming, Multi-view synopsis,
dynamic programming
BibRef
Nie, Y.,
Li, Z.,
Zhang, Z.,
Zhang, Q.,
Ma, T.,
Sun, H.,
Collision-Free Video Synopsis Incorporating Object Speed and Size
Changes,
IP(29), No. , 2020, pp. 1465-1478.
IEEE DOI
1911
Electron tubes, Optimization, Surveillance, Image coding,
Computer science, Sun, Indexes, Surveillance video synopsis,
metropolis sampling
BibRef
Chen, Y.[Yu],
Hu, R.M.[Rui-Min],
Xiao, J.[Jing],
Wang, Z.Y.[Zhong-Yuan],
Multisource surveillance video coding with synthetic reference frame,
JVCIR(65), 2019, pp. 102685.
Elsevier DOI
1912
Surveillance video coding, Global knowledge, Local information, Reference frame
BibRef
Muhammad, K.[Khan],
Hussain, T.[Tanveer],
Baik, S.W.[Sung Wook],
Efficient CNN based summarization of surveillance videos for
resource-constrained devices,
PRL(130), 2020, pp. 370-375.
Elsevier DOI
2002
Video analysis, Video summarization, Surveillance,
Energy-efficiency, Resource-constrained devices
BibRef
Sreeja, M.U.,
Kovoor, B.C.[Binsu C.],
An aggregated deep convolutional recurrent model for event based
surveillance video summarisation: A supervised approach,
IET-CV(15), No. 4, 2021, pp. 297-311.
DOI Link
2106
BibRef
Wu, L.R.[Li-Rong],
Huang, K.J.[Ke-Jie],
Shen, H.B.[Hai-Bin],
Gao, L.L.[Lian-Li],
Foreground-Background Parallel Compression With Residual Encoding for
Surveillance Video,
CirSysVideo(31), No. 7, July 2021, pp. 2711-2724.
IEEE DOI
2107
Video compression, Surveillance, Interpolation, Encoding, Decoding,
Motion estimation, Surveillance video,
video coding
BibRef
Yang, Y.[Yoonsik],
Kim, H.[Haksub],
Choi, H.[Heeseung],
Chae, S.[Seungho],
Kim, I.J.[Ig-Jae],
Scene Adaptive Online Surveillance Video Synopsis via Dynamic Tube
Rearrangement Using Octree,
IP(30), 2021, pp. 8318-8331.
IEEE DOI
2110
Electron tubes, Streaming media, Surveillance,
Heuristic algorithms, Complexity theory, Geometry,
octree-based tube rearrangement
BibRef
Pappalardo, G.[Giovanna],
Allegra, D.[Dario],
Stanco, F.[Filippo],
Battiato, S.[Sebastiano],
A New Framework for Studying Tubes Rearrangement Strategies in
Surveillance Video Synopsis,
ICIP19(664-668)
IEEE DOI
1910
Video Synopsis, Videos Surveillance, Synthetic dataset,
Tubes rearrangement, Graph colouring
BibRef
Durand, T.[Tom],
He, X.[Xiyan],
Pop, I.[Ionel],
Robinault, L.[Lionel],
Utilizing Deep Object Detector for Video Surveillance Indexing and
Retrieval,
MMMod19(II:506-518).
Springer DOI
1901
BibRef
Fang, K.[Kuan],
Wu, T.L.[Te-Lin],
Yang, D.[Daniel],
Savarese, S.[Silvio],
Lim, J.J.[Joseph J.],
Demo2Vec: Reasoning Object Affordances from Online Videos,
CVPR18(2139-2147)
IEEE DOI
1812
Videos, Feature extraction, Robots, Predictive models, YouTube, Decoding.
BibRef
Ravi, H.,
Wang, L.,
Muniz, C.M.,
Sigal, L.,
Metaxas, D.N.,
Kapadia, M.,
Show Me a Story: Towards Coherent Neural Story Illustration,
CVPR18(7613-7621)
IEEE DOI
1812
Pattern recognition
BibRef
Wang, W.,
Zhang, Q.,
Luo, B.,
Tang, J.,
Ruan, R.,
Li, C.,
Selecting attentive frames from visually coherent video chunks for
surveillance video summarization,
ICIP17(2408-2412)
IEEE DOI
1803
Feature extraction, Measurement, Partitioning algorithms,
Support vector machines, Surveillance, Trajectory, Visualization,
video summarization
BibRef
Wang, W.C.,
Chung, P.C.,
Huang, C.R.,
Huang, W.Y.,
Event based surveillance video synopsis using trajectory kinematics
descriptors,
MVA17(250-253)
DOI Link
1708
Cameras, Kinematics, Organizations, Streaming media, Surveillance,
Trajectory, Visualization
BibRef
Panda, R.,
Dasy, A.,
Roy-Chowdhury, A.K.,
Video summarization in a multi-view camera network,
ICPR16(2971-2976)
IEEE DOI
1705
Cameras, Correlation, Dictionaries, Linear programming, Optimization,
Sparse matrices, Symmetric, matrices
BibRef
Annappa, M.[Manish],
Chakravarthy, S.[Sharma],
Athitsos, V.[Vassilis],
Pre-processing of Video Streams for Extracting Queryable Representation
of Its Contents,
ISVC16(II: 301-311).
Springer DOI
1701
inferring situations of interest.
BibRef
Lai, P.K.[Po Kong],
Décombas, M.,
Moutet, K.,
Laganière, R.,
Video summarization of surveillance cameras,
AVSS16(286-294)
IEEE DOI
1611
Acceleration
BibRef
Salehin, M.M.,
Paul, M.,
Summarizing Surveillance Video by Saliency Transition and Moving
Object Information,
DICTA15(1-8)
IEEE DOI
1603
image motion analysis
BibRef
Hoshen, Y.[Yedid],
Peleg, S.[Shmuel],
Live video synopsis for multiple cameras,
ICIP15(212-216)
IEEE DOI
1512
Multi Camera Synopsis; Video Surveillance; Video Synopsis
BibRef
Yun, S.[Sangdoo],
Yun, K.[Kimin],
Kim, S.W.[Soo Wan],
Yoo, Y.J.[Young-Joon],
Jeong, J.[Jiyeoup],
Visual surveillance briefing system:
Event-based video retrieval and summarization,
AVSS14(204-209)
IEEE DOI
1411
Animation
BibRef
Choudhary, V.[Vikas],
Tiwari, A.K.[Anil K.],
Surveillance Video Synopsis,
ICCVGIP08(207-212).
IEEE DOI
0812
BibRef
Li, J.[Jian],
Nikolov, S.G.[Stavri G.],
Benton, C.P.[Christopher P.],
Scott-Samuel, N.E.[Nicholas E.],
Adaptive summarisation of surveillance video sequences,
AVSBS07(546-551).
IEEE DOI
0709
BibRef
Graves, A.,
Gong, S.,
Wavelet-based holistic sequence descriptor for generating video
summaries,
BMVC04(xx-yy).
HTML Version.
0508
BibRef
Earlier:
Spotting Scene Change for Indexing Surveillance Video,
BMVC03(xx-yy).
HTML Version.
0409
BibRef
Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Personal Videos, Consumer Videos, Abstracts, Synopsis, Summarization .