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Anomaly Detection in Road Traffic Using Visual Surveillance: A Survey [article]

Santhosh Kelathodi Kumaran, Debi Prosad Dogra, Partha Pratim Roy
2019 arXiv   pre-print
Since the underlying building block of a typical anomaly detection is learning, we emphasize more on learning methods applied on video scenes.  ...  In this paper, we present a survey on relevant visual surveillance related researches for anomaly detection in public places, focusing primarily on roads.  ...  Hierarchical Dirichlet Process (HDP) [174] A nonparametric Bayesian approach, built based on LDA, to cluster data: Used in data modeling and anomaly detection [78] .  ... 
arXiv:1901.08292v1 fatcat:qehtkb2imfbmpfahkgsjrx7544

Unsupervised learning of micro-action exemplars using a Product Manifold

Stephen O'Hara, Bruce A. Draper
2011 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)  
Further, we show that the system is amenable to incremental learning as anomalous activities are detected in the video stream.  ...  We show how to construct a set of training "tracklets," how to cluster them using a recently introduced Product Manifold distance measure, and how to perform detection using exemplars learned from the  ...  We thank Yui Man Lui for many fruitful discussions about manifold geometry and for sharing his source code.  ... 
doi:10.1109/avss.2011.6027323 dblp:conf/avss/OHaraD11 fatcat:kr66dx7qjbb5ffq5cqqphcrvkm

Crowded Scene Analysis: A Survey

Teng Li, Huan Chang, Meng Wang, Bingbing Ni, Richang Hong, Shuicheng Yan
2015 IEEE transactions on circuits and systems for video technology (Print)  
, and anomaly detection in crowds.  ...  In the past few years, an increasing number of works on crowded scene analysis have been reported, covering different aspects including crowd motion pattern learning, crowd behavior and activity analysis  ...  The unusual events are identified as those dynamic textures with high reconstruction error. e) Manifold Learning Model: In [83] , the manifold learning-based framework has also been applied for the detection  ... 
doi:10.1109/tcsvt.2014.2358029 fatcat:prgoh37gjfcl7n6dp2u6tsdoda

Anomaly Detection and Localization in Crowded Scenes by Motion-field Shape Description and Similarity-based Statistical Learning [article]

Xinfeng Zhang, Su Yang, Xinjian Zhang, Weishan Zhang, Jiulong Zhang
2018 arXiv   pre-print
Furthermore, we propose a K-NN similarity-based statistical model to detect anomalies over time and space, which is an unsupervised one-class learning algorithm requiring no clustering nor any prior assumption  ...  We conduct experiments on real-world surveillance videos, and the results demonstrate that the proposed method can reliably detect and locate the abnormal events in the video sequences, outperforming the  ...  We carried out experiments on two real-world surveillance videos, for anomaly detection and localization, and the results validate the effectiveness of the proposed method.  ... 
arXiv:1805.10620v1 fatcat:bobtxt2zj5hpthh3lyzavvyxmu

A Survey of Deep Learning Solutions for Anomaly Detection in Surveillance Videos

John Gatara Munyua, Geoffrey Mariga Wambugu, Stephen Thiiru Njenga
2021 International Journal of Computer and Information Technology(2279-0764)  
Hence, it has been widely applied to solve complex cognitive tasks like the detection of anomalies in surveillance videos.  ...  Anomaly detection in this case is the identification of abnormal events in the surveillance videos which can be deemed as security incidents or threats.  ...  This learning technique has been applied by Aberkane [37] to detect anomalies in videos. Aberkane and Elarbi used a Deep Q Learning Network (DQN) to locate anomalies in videos.  ... 
doi:10.24203/ijcit.v10i5.166 fatcat:kbqkwer2nvh5jk6gv54xygiueq

Classifying spatiotemporal object trajectories using unsupervised learning of basis function coefficients

Shehzad Khalid, Andrew Naftel
2005 Proceedings of the third ACM international workshop on Video surveillance & sensor networks - VSSN '05  
Applications to motion data mining in video surveillance databases are envisaged.  ...  Encoding trajectories in this way leads to efficiency gains over existing approaches that use discrete point-based flow vectors to represent the whole trajectory.  ...  In [30] , a semantic event detection technique based on discrete HMMs is applied to snooker videos.  ... 
doi:10.1145/1099396.1099404 fatcat:eshvy3oxgvhh5cpawf6rfhyqu4

CLAWS: Clustering Assisted Weakly Supervised Learning with Normalcy Suppression for Anomalous Event Detection [chapter]

Muhammad Zaigham Zaheer, Arif Mahmood, Marcella Astrid, Seung-Ik Lee
2020 Lecture Notes in Computer Science  
Learning to detect real-world anomalous events through video-level labels is a challenging task due to the rare occurrence of anomalies as well as noise in the labels.  ...  In this work, we propose a weakly supervised anomaly detection method which has manifold contributions including1) a random batch based training procedure to reduce inter-batch correlation, 2) a normalcy  ...  Anomalies are then detected based on their distinction from the learned normalities.  ... 
doi:10.1007/978-3-030-58542-6_22 fatcat:jwaaxl2ajrfc3ehlazdzjpokcq

Using a Product Manifold distance for unsupervised action recognition

Stephen O'Hara, Yui Man Lui, Bruce A. Draper
2012 Image and Vision Computing  
We show how to construct a set of training "tracklets," how to cluster them using the Product Manifold distance measure, and how to perform detection using exemplars learned from the clusters.  ...  Further, we show that the system is amenable to incremental learning as anomalous activities are detected in the video stream.  ...  Acknowledgments We would like to thank Piotr Dollár for the Bag-of-Features code he has made available.  ... 
doi:10.1016/j.imavis.2011.11.001 fatcat:62bakb2y2vfwzexlw5g4ah4zvq

Anomaly Detection in Surveillance Video of Natural Environment

Silas Santiago L. Pereira, José E.B. Maia
2021 International Journal of Computer Applications  
This work demonstrates the effectiveness of the median filter combined with morphological operators in the detection of anomalies in video surveillance of scenes of natural environment.  ...  The performance on four publicly available benchmark videos is compared to that of other published state-of-the-art works. The results obtained are promising.  ...  CONCLUSION This work presented an approach to detect anomalies in video surveillance of natural environments.  ... 
doi:10.5120/ijca2021921288 fatcat:raghxuzwzvewziualaezdoguvu

An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videos [article]

B Ravi Kiran, Dilip Mathew Thomas, Ranjith Parakkal
2018 arXiv   pre-print
This article reviews the state-of-the-art deep learning based methods for video anomaly detection and categorizes them based on the type of model and criteria of detection.  ...  We also perform simple studies to understand the different approaches and provide the criteria of evaluation for spatio-temporal anomaly detection.  ...  Adversarial Discriminators using Cross-channel prediction Here we shall review the work done in [68] applied to anomaly detection in videos.  ... 
arXiv:1801.03149v2 fatcat:u6qz7upzfbdgfaxvihpl55kdhi

Deep Learning for Anomaly Detection: A Review [article]

Guansong Pang, Chunhua Shen, Longbing Cao, Anton van den Hengel
2020 arXiv   pre-print
In recent years, deep learning enabled anomaly detection, i.e., deep anomaly detection, has emerged as a critical direction.  ...  Anomaly detection, a.k.a. outlier detection, has been a lasting yet active research area in various research communities for several decades.  ...  Similar approaches can also be found in graph anomaly detection [169] , in which unsupervised clustering-based anomaly measures are used in the latent representation space to calculate the abnormality  ... 
arXiv:2007.02500v2 fatcat:ezrirm4rxvbi3hqcd23adzmhou

Activity Analysis in Complicated Scenes Using DFT Coefficients of Particle Trajectories

Jingxin Xu, Simon Denman, Sridha Sridharan, Clinton Fookes
2012 2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance  
We propose a novel approach to analyse activities in crowded scenes using a "bag of particle trajectories".  ...  Our applications include temporal video segmentation and anomaly detection, and we perform our evaluation on several real-world datasets containing complicated scenes.  ...  The proposed approach has been applied to both anomaly detection and temporal video segmentation, and state-of-the-art performance is achieved.  ... 
doi:10.1109/avss.2012.6 dblp:conf/avss/XuDSF12 fatcat:jremlbqzojbx5l3ppohw7aqap4

Abnormal Crowd behavior Detection Using Structural Context Descriptor

Poo ja, Sarvesh Vishwakarma
2016 Bonfring International Journal of Advances in Image Processing  
The approach presents the abnormal behavior detection method from the crowd scenes to efficiently detect anomalies present in the crowded scenes.  ...  In concern with the people safety in public places, an Abnormal Behavior Detection in crowded scene has gained popularity. The Abnormal Behavior Detection is an active area of research.  ...  Manifold Learning Model: The manifold learning based structure are been enforced for unusual event detection in crowded scene.  ... 
doi:10.9756/bijaip.10466 fatcat:xm7jmhsxsvakleckrrau22ocqy

Exploring Techniques for Vision Based Human Activity Recognition: Methods, Systems, and Evaluation

Xin Xu, Jinshan Tang, Xiaolong Zhang, Xiaoming Liu, Hong Zhang, Yimin Qiu
2013 Sensors  
With the wide applications of vision based intelligent systems, image and video analysis technologies have attracted the attention of researchers in the computer vision field.  ...  In the past, a large number of papers have been published on human activity recognition in video and image sequences.  ...  This work was supported in part by the Project from Science  ... 
doi:10.3390/s130201635 pmid:23353144 pmcid:PMC3649413 fatcat:pssdgo3rpbak7czx6zn47rvjla

An Overview of Deep Learning Based Methods for Unsupervised and Semi-Supervised Anomaly Detection in Videos

B. Kiran, Dilip Thomas, Ranjith Parakkal
2018 Journal of Imaging  
This article reviews the state-of-the-art deep learning based methods for video anomaly detection and categorizes them based on the type of model and criteria of detection.  ...  We also perform simple studies to understand the different approaches and provide the criteria of evaluation for spatio-temporal anomaly detection.  ...  Acknowledgments : The authors would like to thank Benjamin Crouzier for his help in proof reading the manuscript, and Y. Senthil Kumar (Valeo) for helpful suggestions.  ... 
doi:10.3390/jimaging4020036 fatcat:za52zspzjbewbakdordavpatvq
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