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A Modular and Unified Framework for Detecting and Localizing Video Anomalies [article]

Keval Doshi, Yasin Yilmaz
2021 arXiv   pre-print
plug-and-play architecture, a sequential anomaly detector, a mathematical framework for selecting the detection threshold, and a suitable performance metric for real-time anomalous event detection in  ...  event detection.  ...  In summary, our contributions in this paper are as follows: • We present a systematic unified framework for online event detection and offline frame localization for video anomalies, and propose a new  ... 
arXiv:2103.11299v1 fatcat:cqip5pyg5bfzfgiocrmrr252p4

Joint Detection and Recounting of Abnormal Events by Learning Deep Generic Knowledge

Ryota Hinami, Tao Mei, Shin'ichi Satoh
2017 2017 IEEE International Conference on Computer Vision (ICCV)  
Our approach first learns CNN with multiple visual tasks to exploit semantic information that is useful for detecting and recounting abnormal events.  ...  Our approach outperforms the stateof-the-art on Avenue and UCSD Ped2 benchmarks for abnormal event detection and also produces promising results of abnormal event recounting.  ...  This paper presents a framework that jointly detects and recounts abnormal events by integrating generic and environment-specific knowledge into a unified framework.  ... 
doi:10.1109/iccv.2017.391 dblp:conf/iccv/HinamiMS17 fatcat:hgwrqpuxqnfwxeetg6afjmcqqy

Joint Detection and Recounting of Abnormal Events by Learning Deep Generic Knowledge [article]

Ryota Hinami, Tao Mei, Shin'ichi Satoh
2017 arXiv   pre-print
Our approach first learns CNN with multiple visual tasks to exploit semantic information that is useful for detecting and recounting abnormal events.  ...  Our approach outperforms the state-of-the-art on Avenue and UCSD Ped2 benchmarks for abnormal event detection and also produces promising results of abnormal event recounting.  ...  This paper presents a framework that jointly detects and recounts abnormal events by integrating generic and environment-specific knowledge into a unified framework.  ... 
arXiv:1709.09121v1 fatcat:ecuzpw6yxvcktgqcx2v4mc4snm

Panic Detection in Crowded Scenes

A. B. Altamimi, H. Ullah
2020 Zenodo  
The proposed method was evaluated considering two benchmark datasets and outperformed five existing methods.  ...  In order to handle this challenge, this paper proposes the integration of different features into a unified model.  ...  This framework renders a deep insight into the optimal feature extraction for anomaly detection.  ... 
doi:10.5281/zenodo.3748322 fatcat:3en2u23zpvgwnk6yy2ak7dbtzu

People and vehicles in danger - A fire and flood detection system in social media

Panagiotis Giannakeris, Konstantinos Avgerinakis, Anastasios Karakostas, Stefanos Vrochidis, Ioannis Kompatsiaris
2018 Zenodo  
This paper presents a novel warning system framework for detecting people and vehicles in danger.  ...  solving crisis events.  ...  The same framework has also been deployed in UA-DETRAC vehicle detection dataset [18] , achieving a really high detection rate.  ... 
doi:10.5281/zenodo.1243993 fatcat:qixb3cngd5gqhddsjqitmg33dy

A Comprehensive Review of Group Activity Recognition in Videos

Li-Fang Wu, Qi Wang, Meng Jian, Yu Qiao, Bo-Xuan Zhao
2021 International Journal of Automation and Computing  
First, we provide a summary and comparison of 11 GAR video datasets in this field.  ...  AbstractHuman group activity recognition (GAR) has attracted significant attention from computer vision researchers due to its wide practical applications in security surveillance, social role understanding  ...  representation for event detection.  ... 
doi:10.1007/s11633-020-1258-8 fatcat:ycka4thcy5a6vghpenpthtrndi

PETS2009: Dataset and challenge

J. Ferryman, A. Shahrokni
2009 2009 Twelfth IEEE International Workshop on Performance Evaluation of Tracking and Surveillance  
A new section 2.1 on Benchmark Design has been added to include details on the general challenges in designing benchmarked datasets for the surveillance community.  ...  Benchmark Design 53 The challenges in creating benchmark datasets for the performance eval-54 uation of automated visual surveillance methods are broad.  ... 
doi:10.1109/pets-winter.2009.5399556 fatcat:kwi7fui5mvev7khywikw54lgcq

A Research on Multi-View Video Summarization Techniques

2019 International Journal of Engineering and Advanced Technology  
Generating Summary for Surveillance videos is more challenging because, videos Captured by surveillance cameras is long, contains uninteresting events, same scene recorded in different views leading to  ...  , educational institutions, Offices, Hospitals are equipped with multiple surveillance cameras having overlapping field of view for security and environment monitoring purposes.  ...  Event Bagging, Ensemble Video Summarization: Table 2 Table 1 : 21 Benchmark dataset description Dataset No of views Durations (mins) Office 4 46:19 Lobby 3 24:42 BL-7F 19 136:10 Table  ... 
doi:10.35940/ijeat.a2985.109119 fatcat:2nznlbqinnek5d2a7ymeawbuvq

Pedestrian Detection and Tracking in Video Surveillance System: Issues, Comprehensive Review, and Challenges [chapter]

Ujwalla Gawande, Kamal Hajari, Yogesh Golhar
2020 Computational Intelligence [Working Title]  
Pedestrian detection and monitoring in a surveillance system are critical for numerous utility areas which encompass unusual event detection, human gait, congestion or crowded vicinity evaluation, gender  ...  A brief summary of surveillance system along with comparisons of pedestrian detection and tracking technique in video surveillance is presented in this chapter.  ...  A general framework of automated visual surveillance system is shown in Figure 2 [7] [8] [9] .  ... 
doi:10.5772/intechopen.90810 fatcat:y2shras2ivfsdjj67jpruhdiyy

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.  ...  General outdoor surveillance benchmark datasets and online evaluation service were provided in this workshop for the participants to evaluate their systems.  ... 
doi:10.3390/s130201635 pmid:23353144 pmcid:PMC3649413 fatcat:pssdgo3rpbak7czx6zn47rvjla

MOR-UAV: A Benchmark Dataset and Baselines for Moving Object Recognition in UAV Videos [article]

Murari Mandal, Lav Kush Kumar, Santosh Kumar Vipparthi
2020 arXiv   pre-print
We assigned the labels for two categories of vehicles (car and heavy vehicle). Furthermore, we propose a deep unified framework MOR-UAVNet for MOR in UAV videos.  ...  Since, this is a first attempt for MOR in UAV videos, we present 16 baseline results based on the proposed framework over the MOR-UAV dataset through quantitative and qualitative experiments.  ...  ACKNOWLEDGEMENTS The authors are highly grateful to IBM for providing with online GPU grant. The work was also supported by the DST-SERB project #EEQ/2017/000673.  ... 
arXiv:2008.01699v2 fatcat:hglqmhxmmzaqje5docjyq6q7dy

Survey on Deep Learning-Based Marine Object Detection

Ruolan Zhang, Shaoxi Li, Guanfeng Ji, Xiuping Zhao, Jing Li, Mingyang Pan, Chunjia Han
2021 Journal of Advanced Transportation  
We present a survey on marine object detection based on deep neural network approaches, which are state-of-the-art approaches for the development of autonomous ship navigation, maritime surveillance, shipping  ...  A widely accepted and standardized large-scale marine object verification dataset should be proposed.  ...  Acknowledgments is work was supported in part by the Fundamental Research Funds for the Central Universities, Grant nos. 3132021130 and 3132019400.  ... 
doi:10.1155/2021/5808206 fatcat:y3epygwit5efxnlhv4hp7uodqy

Audio-visual Representation Learning for Anomaly Events Detection in Crowds [article]

Junyu Gao, Maoguo Gong, Xuelong Li
2021 arXiv   pre-print
We conduct the experiments on SHADE dataset, a synthetic audio-visual dataset in surveillance scenes, and find introducing audio signals effectively improves the performance of anomaly events detection  ...  Compare with vision information that is easily occluded, audio signals have a certain degree of penetration.  ...  The video clips in these two datasets are gained from movies and videos on internet. [42] is a typical method for video classification with VSD benchmark.  ... 
arXiv:2110.14862v1 fatcat:cxhpmy3irbgblkpoxlcmmajp6i

ReMotENet: Efficient Relevant Motion Event Detection for Large-scale Home Surveillance Videos [article]

Ruichi Yu, Hongcheng Wang, Larry S. Davis
2018 arXiv   pre-print
To dramatically speedup relevant motion event detection and improve its performance, we propose a novel network for relevant motion event detection, ReMotENet, which is a unified, end-to-end data-driven  ...  It can detect relevant motion on a 15s surveillance video clip within 4-8 milliseconds on a GPU and a fraction of second (0.17-0.39) on a CPU with a model size of less than 1MB.  ...  Partial support from the Office of Naval Research under Grant N000141612713 (Visual Common Sense Reasoning for Multiagent Activity Prediction and Recognition) is acknowledged.  ... 
arXiv:1801.02031v1 fatcat:ksfahktdlvhuvhzxks4atoebrq

A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance

Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
2021 Computers  
In this work, we give an overview of non-specific syndromic surveillance from the perspective of machine learning and propose a unified framework based on global and local modeling techniques.  ...  We also present a set of statistical modeling techniques which have not been used in a local modeling context before and can serve as benchmarks for the more elaborate machine learning approaches.  ...  (2) We present a local and a global modeling strategy for non-specific syndromic surveillance in an unified framework.  ... 
doi:10.3390/computers10030032 fatcat:dbbfbdmbxzbbvmmoyamhq4llce
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