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Group Event Detection with a Varying Number of Group Members for Video Surveillance
[article]
2015
arXiv
pre-print
Preserved Fulltext
This paper presents a novel approach for automatic recognition of group activities for video surveillance applications. ...
We propose to use a group representative to handle the recognition with a varying number of group members, and use an Asynchronous Hidden Markov Model (AHMM) to model the relationship between people. ...
Acknowle (W911NF-05-1-0491) an amy Dengio for providing part of the code for implementing the AHMM. ...
arXiv:1503.00082v1
fatcat:242kbltfbfdyjnpg2ano6r2ho4
Group Event Detection With a Varying Number of Group Members for Video Surveillance
2010
IEEE transactions on circuits and systems for video technology (Print)
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This paper presents a novel approach for automatic recognition of group activities for video surveillance applications. ...
We propose to use a group representative to handle the recognition with a varying number of group members, and use an asynchronous hidden Markov model (AHMM) to model the relationship between people. ...
Dengio for providing part of the code for implementing the AHMM. ...
doi:10.1109/tcsvt.2010.2057013
fatcat:wislqkv345gmjftbg4qs7rmeae
Motion Based Summarization and Grouping of Events for Video Surveillance System
2014
International Journal of Engineering Research
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Motion Based Summarization and Grouping of Events for Video Surveillance is one o f the approach for detecting dynamic and complex scenes in computer vision. ...
Furthermore we propose a grouping of events people running together, fighting, etc. This method can handle both symmetric and asymmetric group activities. ...
In this paper, we address the following issues for group event detection. i. Group Event Detection with a Vary ing Number of Group Members. ii. ...
doi:10.17950/ijer/v3s4/417
fatcat:cbg2avpkvffcpksvyadkjylus4
Group event detection for video surveillance
2009
2009 IEEE International Symposium on Circuits and Systems
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This paper presents a novel approach for automatic recognition of group activities for video surveillance applications. ...
We propose to use a group representative to handle the recognition with flexible or varying number of group members, and use an Asynchronous Hidden Markov Model (AHMM) to model the relationship between ...
Samy Dengio for providing part of the code for implementing the AHMM. ...
doi:10.1109/iscas.2009.5118391
dblp:conf/iscas/LinSPZ09
fatcat:ddrmix7xgnemxftkc3akgfat4e
Detecting shopper groups in video sequences
2007
2007 IEEE Conference on Advanced Video and Signal Based Surveillance
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The results demonstrate the ability of our method to detect such activities in congested surveillance videos. ...
In particular in three hours of indoor retail store video, our method has correctly identified over 85% of valid "'shopper-groups"' with a very low level of false positives, validated against human coded ...
We present a framework to detect so-called "shopper groups" in tracked video sequences of retail stores. ...
doi:10.1109/avss.2007.4425347
dblp:conf/avss/LeykinT07
fatcat:f4njntwzzraufawdg2d34glv7m
ViCoMo: visual context modeling for scene understanding in video surveillance
2013
Journal of Electronic Imaging (JEI)
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.; de With, P.H.N. Abstract. The use of contextual information can significantly aid scene understanding of surveillance video. ...
We propose a proof-of-concept system that uses several sources of contextual information to improve scene understanding in surveillance video. ...
Acknowledgments This work has been performed in the framework of the ITEA2 ViCoMo Project, cofunded by grants from The Netherlands, Finland, France, Spain, and Turkey. ...
doi:10.1117/1.jei.22.4.041117
fatcat:r4xrshxhmrcrha6eircgtem4aa
Novel Group Detection and Analysis Method Based on Automatic and Fast Density Clustering
2016
Proceedings of the 22nd International Conference on Distributed Multimedia Systems
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Group-level crowd behavior analysis is a new and promising method with important applications for the video surveillance and understanding of crowds. ...
This detection method is more adaptive to groups with arbitrary shapes and varying densities because the group core is refined with coherent neighbors. ...
Further research is needed, such as video surveillance to define and detect group events and characterizing people to divide a group into three level. ...
doi:10.18293/dms2016-019
dblp:conf/dms/JinBX16
fatcat:ig7jzbaowvcndohfu7xlekiobm
A Generic Framework for Video Understanding Applied to Group Behavior Recognition
2012
2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance
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This paper presents an approach to detect and track groups of people in video-surveillance applications, and to automatically recognize their behavior. ...
This method keeps track of individuals moving together by maintaining a spacial and temporal group coherence. First, people are individually detected and tracked. ...
Acknowledgment This work was supported partly by the Video-Id, ViCoMo, Vanaheim, and Support projects. ...
doi:10.1109/avss.2012.1
dblp:conf/avss/ZaidenbergBB12
fatcat:wfhk5zbpijbephkk4hnyhnetki
Group Tracking and Behavior Recognition in Long Video Surveillance Sequences
english
2014
Proceedings of the 9th International Conference on Computer Vision Theory and Applications
english
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This paper makes use of recent advances in group tracking and behavior recognition to process large amounts of video surveillance data from an underground railway station and perform a statistical analysis ...
We present the results and interpretation of one month of processed data from a video surveillance camera in the Torino subway. ...
This paper presents an approach for group tracking and behavior recognition in a subway station applied to long video surveillance sequences (around 2 hours per video). ...
doi:10.5220/0004682503960402
dblp:conf/visapp/GarateZBB14
fatcat:pbrdjdzyfrbuvim4fj5pq5xza4
Video Anomaly Search in Crowded Scenes via Spatio-Temporal Motion Context
2013
IEEE Transactions on Information Forensics and Security
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Video anomaly detection plays a critical role for intelligent video surveillance. We present an abnormal video event detection system that considers both spatial and temporal contexts. ...
For anomaly measurements, we formulate the abnormal event detection as a matching problem, which is more robust than statistic model based methods, especially when the training dataset is of limited size ...
Abstract-Video anomaly detection plays a critical role for intelligent video surveillance. We present an abnormal video event detection system that considers both spatial and temporal contexts. ...
doi:10.1109/tifs.2013.2272243
fatcat:raxlrmdkv5bhvp24xa2zw6ngfa
Adabev: Automatic Detection Of Abnormal Behavior In Video-Surveillance
2012
Zenodo
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We present in this paper ADABeV, an intelligent video-surveillance framework for event recognition in crowded scene to detect the abnormal human behaviour. ...
The analysis and recognition of abnormal behaviours in a video sequence has gradually drawn the attention in the field of IVS, since it allows filtering out a large number of useless information, which ...
They proposed to use a group representative to handle the recognition with flexible or varying number of group members, and use an Asynchronous Hidden Markov Model (AHMM) to model the relationship between ...
doi:10.5281/zenodo.1057171
fatcat:aa2ukdfzujawdpn73rrqwdljpm
Team activity analysis and recognition based on Kinect depth map and optical imagery techniques
2012
Signal Processing, Sensor Fusion, and Target Recognition XXI
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Kinect cameras produce low-cost depth map video streams applicable for conventional surveillance systems. ...
A Casual-Events State Inference (CESI) technique is proposed for spatiotemporal recognition and reasoning of group activities. ...
ACKNOWLEDGMENTS This work has been supported by a Multidisciplinary University Research Initiative (MURI) grant (Number W911NF-09-1-0392) for "Unified Research on Network-based Hard/Soft Information Fusion ...
doi:10.1117/12.919946
fatcat:dzsqcit46nhhhplfgx7eqgyhte
Video surveillance: past, present, and now the future [DSP Forum]
2013
IEEE Signal Processing Magazine
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James Ferryman: I agree, applications for video surveillance vary widely. ...
Ideally, we would like to search videos with computers to detect events of interest, but with rare notable exceptions, the promise of video content analysis has not been realized. ...
Proceedings of the IEEE. Subscribe today. www.ieee.org/proceedings ...
doi:10.1109/msp.2013.2241312
fatcat:th7r5vwudjgujkelm4xzfeftfa
Group context learning for event recognition
2012
2012 IEEE Workshop on the Applications of Computer Vision (WACV)
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We address the problem of group-level event recognition from videos. The events of interest are defined based on the motion and interaction of members in a group over time. ...
Finally, our method uses the learned Support Vector Machine (SVM) to classify a video segment into the six event categories. ...
We designed robust features that can capture the group context of individuals in a video. We built a system with the proposed algorithm, which can process a video and detect the events in real-time. ...
doi:10.1109/wacv.2012.6163009
dblp:conf/wacv/ZhangGCL12
fatcat:3jworwspcfbkfnbhpkbv7pti5y
Crowd Anomaly Detection for Automated Video Surveillance
2015
6th International Conference on Imaging for Crime Prevention and Detection (ICDP-15)
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This new approach is envisaged to facilitate a wide spectrum of crowd analysis applications through automating current Closed-Circuit Television (CCTV)-based surveillance systems. ...
Through extracting and integrating those crowd textures from surveillance recordings, a redundancy wavelet transformation-based feature space can be deployed for behavioural template matching. ...
System framework of real-time anomaly crowd event detection algorithmAs illustrated in Figure5, the system starts from building up a video buffer only containing certain number of video frames before STV ...
doi:10.1049/ic.2015.0102
dblp:conf/icdp/0033X15
fatcat:vnm47zjowfg6pjqzlq6itfp45i
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