19.4.5.6.1 Surveillance Video Summarization, Surveillance Synopsis

Chapter Contents (Back)
Video Abstracts. Video Summarization. Surveillance. Summarization.

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.[Anni], 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., 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

Kumar, K.[Krishan],
EVS-DK: Event video skimming using deep keyframe,
JVCIR(58), 2019, pp. 345-352.
Elsevier DOI 1901
Clustering, Deep learning, Event summarization, Highly connected subgraph, Key-frames, Video, Graph 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


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
Computer vision, 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 .


Last update:Apr 20, 2019 at 12:32:38