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Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection
[article]
2021
arXiv
pre-print
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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
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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
2013
IEEE transactions on circuits and systems for video technology (Print)
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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
2021
Journal of Healthcare Engineering
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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
2014
Pattern Recognition Letters
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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
2019
Computers in Biology and Medicine
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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]
2021
Smart and Pervasive Healthcare [Working Title]
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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
2014
Technologies
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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
2022
Zenodo
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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
2021
Sensors
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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]
2020
bioRxiv
pre-print
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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
2017
International Journal of Artificial Intelligence in Education
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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
2020
Sensors
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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
2018
Journal of Sensor and Actuator Networks
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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]
2021
arXiv
pre-print
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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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