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Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection [article]

Shoubin Yu, Zhongyin Zhao, Haoshu Fang, Andong Deng, Haisheng Su, Dongliang Wang, Weihao Gan, Cewu Lu, Wei Wu
2021 arXiv   pre-print
Anomaly detection in surveillance videos is challenging and important for ensuring public security.  ...  These two modules are then integrated into a unified framework for pose regularity learning, which is referred to as Motion Prior Regularity Learner (MoPRL).  ...  Related Works Self-supervised Video Anomaly Detection In self-supervised video anomaly detection, anomalies are recognized as outliers of the distribution of normality.  ... 
arXiv:2112.03649v2 fatcat:wgdridft3zaenls7kts5badtbq

2021 Index IEEE Transactions on Multimedia Vol. 23

2021 IEEE transactions on multimedia  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TMM 2021 3931-3942 Anomaly detection Multi-Encoder Towards Effective Anomaly Detection in Videos.  ...  ., +, TMM 2021 1442-1453 Spatial-Temporal Cascade Autoencoder for Video Anomaly Detection in Crowded Scenes.  ... 
doi:10.1109/tmm.2022.3141947 fatcat:lil2nf3vd5ehbfgtslulu7y3lq

Video-Based Human Behavior Understanding: A Survey

Paulo Vinicius Koerich Borges, Nicola Conci, Andrea Cavallaro
2013 IEEE transactions on circuits and systems for video technology (Print)  
The advantages and the drawbacks of the methods are critically discussed, providing a comprehensive coverage of key aspects of video-based human behavior understanding, available datasets for experimentation  ...  Human behavior understanding combines image and signal processing, feature extraction, machine learning and 3D geometry.  ...  anomaly detection.  ... 
doi:10.1109/tcsvt.2013.2270402 fatcat:ilpqptjrhfacjasyyw6wfug7ia

Home Interactive Elderly Care Two-Way Video Healthcare System Design

Chun Yi, Xiqiang Feng, Yi-Zhang Jiang
2021 Journal of Healthcare Engineering  
The key features of the human skeleton are extracted from the model of abnormal leaning and falling behaviour of the elderly, and the SVM machine learning method is used to classify and identify the data  ...  This paper explores and analyses the interactive home geriatric two-way video health care system, investigates and analyses the daily lives and behaviours of the elderly in their homes through research  ...  C and the value of the kernel function parameter g are related to the performance of the model, i.e., the accuracy of anomaly detection.  ... 
doi:10.1155/2021/6693617 pmid:33542800 pmcid:PMC7843169 fatcat:queum3zwxnfofaqwtmliqokwxa

A review of unsupervised feature learning and deep learning for time-series modeling

Martin Längkvist, Lars Karlsson, Amy Loutfi
2014 Pattern Recognition Letters  
This paper gives a review of the recent developments in deep learning and unsupervised feature learning for time-series problems.  ...  While these techniques have shown promise for modeling static data, such as computer vision, applying them to time-series data is gaining increasing attention.  ...  A similar setup was used by Wulsin et al. (2011) for modeling single channel EEG waveforms used for anomaly detection.  ... 
doi:10.1016/j.patrec.2014.01.008 fatcat:zhc3pdwxhbhztnjqyrwpuofp6q

High throughput automated detection of axial malformations in Medaka embryo

Diane Genest, Elodie Puybareau, Marc Léonard, Jean Cousty, Noémie De Crozé, Hugues Talbot
2019 Computers in Biology and Medicine  
We built and validated our learning model on 1459 images with a 10-fold cross-validation by comparison with the gold standard of 3D observations performed under a microscope by a trained operator.  ...  After image acquisition, segmentation tools are used to detect the embryo before analysing several morphological features.  ...  spine as an explicit function.  ... 
doi:10.1016/j.compbiomed.2018.12.016 pmid:30654166 fatcat:nen2k7fv7fhbfkfbb52zk7bgca

VIGOR: A Versatile, Individualized and Generative ORchestrator to Motivate the Movement of the People with Limited Mobility [chapter]

Yu Liang, Dalei Wu, Dakila Ledesma, Zibin Guo, Erkan Kaplanoglu, Anthony Skjellum
2021 Smart and Pervasive Healthcare [Working Title]  
Aiming at developing a deep-learning-enabled rehab and fitness modality through infusing the domain knowledge (physical therapy, medical anthropology, psychology, electrical engineering, bio-mechanics,  ...  Pushing and Coaching (HPC) functions by following Tai-Chi kinematics, the VIGOR system is designed to make engagement in physical activity an affordable, individually engaging, and enjoyable experience for  ...  As an effective deep generative model, Generative Adversarial Networks (GANs) learn to model distribution either with or without supervision for high dimensional data (images, texts, audios, etc.), and  ... 
doi:10.5772/intechopen.96025 fatcat:spfs7eix5renxgua26c2xtqwim

Development of a Large, Low-Cost, Instant 3D Scanner

Jeremy Straub, Scott Kerlin
2014 Technologies  
It discusses multiple prospective uses for the unit and technology. It also provides an overview of future directions of the project, such as 3D video capture.  ...  This paper presents the design of a 3D scanner that was designed and constructed at the University of North Dakota to create 3D models for printing and numerous other uses.  ...  Scanning of human feet to detect anomalies and differences between and across populations has also been performed [5] .  ... 
doi:10.3390/technologies2020076 fatcat:2xeijj2y3fc6novnt45u3334z4

State of the Art of Audio- and Video-Based Solutions for AAL

Slavisa ALeksic, Michael Atanasov, Jean Calleja Agius, Kenneth Camilleri, Anto Čartolovni, Pau Climent-Pérez, Sara Colantonio, Stefania Cristina, Vladimir Despotovic, Hazım Kemal Ekenel, Ekrem Erakin, Francisco Florez-Revuelta (+27 others)
2022 Zenodo  
The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action.  ...  In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness.  ...  Once this is done, a decision tree regression model (C4.5) is used in order to compute an anomaly level and an anomaly score.  ... 
doi:10.5281/zenodo.6390708 fatcat:6qfwqd2v2rhe5iuu5zgz77ay4i

A Survey of Methods and Technologies Used for Diagnosis of Scoliosis

Ilona Karpiel, Adam Ziębiński, Marek Kluszczyński, Daniel Feige
2021 Sensors  
By outlining and categorizing each method, we summarize relevant publications that may not only help introduce other researchers to the field but also be a valuable source for studying existing methods  ...  Segmentation of Paraspinal Muscles at Varied Lumbar Spinal Levels by Explicit Saliency-Aware Learning.  ...  Multiple Axial Spine Indices Estimation via Dense Enhancing Network with Cross-Space Distance-Preserving Regularization. IEEE J. Biomed. Health Inform. 2020, 24, 3248–3257.  ... 
doi:10.3390/s21248410 pmid:34960509 pmcid:PMC8707023 fatcat:m3p7dai57ncqfdxt3eydfmnlay

Automatic tracking of mouse social posture dynamics by 3D videography, deep learning and GPU-accelerated robust optimization [article]

Christian L Ebbesen, Robert C Froemke
2020 bioRxiv   pre-print
We present a hardware/software system that combines 3D videography, deep learning, physical modeling and GPU-accelerated robust optimization.  ...  Currently, most studies of social behavior rely on labor-intensive methods such as manual annotation of individual video frames.  ...  an explicit body model of the animal.  ... 
doi:10.1101/2020.05.21.109629 fatcat:it2g7jctjzgzlafeucfglbpa4a

Detecting and Addressing Frustration in a Serious Game for Military Training

Jeanine A. DeFalco, Jonathan P. Rowe, Luc Paquette, Vasiliki Georgoulas-Sherry, Keith Brawner, Bradford W. Mott, Ryan S. Baker, James C. Lester
2017 International Journal of Artificial Intelligence in Education  
Tutoring systems that are sensitive to affect show considerable promise for enhancing student learning experiences.  ...  engagement and improve learning.  ...  Appendix: Feedback Messages For Experiment #2 Condition 1: Control-Value Theory  ... 
doi:10.1007/s40593-017-0152-1 fatcat:joayrzlf7zhx7hqku65hervtya

Toward Mass Video Data Analysis: Interactive and Immersive 4D Scene Reconstruction

Matthias Kraus, Thomas Pollok, Matthias Miller, Timon Kilian, Tobias Moritz, Daniel Schweitzer, Jürgen Beyerer, Daniel Keim, Chengchao Qu, Wolfgang Jentner
2020 Sensors  
This paper presents the VICTORIA Interactive 4D Scene Reconstruction and Analysis Framework ("ISRA-4D" 1.0), an approach for the visual consolidation of heterogeneous video and image data in a 3D reconstruction  ...  Additional information on video and image content is also extracted and displayed and can be analyzed with supporting visualizations.  ...  Third, tracks of persons and objects are extracted using machine learning models.  ... 
doi:10.3390/s20185426 pmid:32971822 pmcid:PMC7570841 fatcat:cwkd5exbovb2hgtqq6dag7yzdy

Sensors and Actuators in Smart Cities

Mohammad Hammoudeh, Mounir Arioua
2018 Journal of Sensor and Actuator Networks  
Author Contributions: Alex Adim Obinikpo and Burak Kantarci conceived and pursued the literature survey on deep learning techniques on big sensed data for smart health applications, reviewed the state  ...  Ateya and Ammar Muthanna built the network model and perform the simulation process.  ...  Anomaly detection over noisy data using learned probability distributions. In Proceedings of the International Conference on Machine Learning, Citeseer, Stanford, CA, USA, 29 June-2 July 2000. 17.  ... 
doi:10.3390/jsan7010008 fatcat:pt7nkf4oaraijkmsndohahqtnq

Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities [article]

Kaixuan Chen, Dalin Zhang, Lina Yao, Bin Guo, Zhiwen Yu, Yunhao Liu
2021 arXiv   pre-print
In this study, we present a survey of the state-of-the-art deep learning methods for sensor-based human activity recognition.  ...  We first introduce the multi-modality of the sensory data and provide information for public datasets that can be used for evaluation in different challenge tasks.  ...  For instance, in a Parkinson disease detection system, anomaly only appears in gait in a short period instead of the entire time window [172] .  ... 
arXiv:2001.07416v2 fatcat:km2b3xn4sngtxgkdck6ymlmu3m
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