A Survey of the Techniques for The Identification and Classification of Human Actions from Visual Data

Saif, Shahela; Tehseen, Samabia; Kausar, Sumaira

doi:10.3390/s18113979

Cited by 11 publications

(11 citation statements)

References 119 publications

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“…There is an activity level after the action level. Detection of human activity is the process of correctly identifying the action performed 38 . This level has various applications in the fields of video surveillance, human‐computer interaction, health care and sports analysis 35 .…”

Section: Human Behavior Analysismentioning

confidence: 99%

“…In particular, HBA is an important part of computer vision research dedicated to the detection, monitoring and understanding of human physical behavior 37 . Human‐computer interaction has become one of the research topics in video processing 36,38,39 . The HBA phases of video include human detection, human tracking, and human action detection, respectively 38 .…”

Section: Human Behavior Analysismentioning

confidence: 99%

See 1 more Smart Citation

A systematic survey of data mining and big data in human behavior analysis: Current datasets and models

Ding

Gan

Bahrami

2022

Trans Emerging Tel Tech

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In recent years, understanding human behavior has become one of the most important topics in the field of computer vision research. The reason for this growing attention is the wide range of applications that can benefit from the results of this field of research. The human behavior analysis (HBA) includes a wide range of research areas from the detection of human motion and action.Datasets created through actions and detection of human activities make it possible to compare different detection methods with the same input data. Data mining and big data approaches are very popular for analyzing data related to human behavior and can be used to address the challenges of fast processing. This article provides a systematic survey of data mining and big data in the HBA. We focus on current datasets and models related to the detection of human behavior patterns in the literature. The purpose of this survey is to assist researchers in select appropriate datasets and models to evaluate algorithms, as well as to identify research gaps for future work. To achieve this goal, articles published between 2010 and 2021 have been reviewed. These articles fall into five general categories in terms of dataset focus: object detection, motion, action, activity, and behavior. This article provides a summary of data mining and big data models in the HBA, as well as related datasets based on these categories, to highlight promising research avenues for future work.

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Section: Human Behavior Analysismentioning

confidence: 99%

Section: Human Behavior Analysismentioning

confidence: 99%

A systematic survey of data mining and big data in human behavior analysis: Current datasets and models

Ding

Gan

Bahrami

2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

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“…More comprehensive details of action recognition, motion analysis, and body tracking can be also found in [ 131 , 132 , 133 , 134 , 135 ]. Some state-of-the-art works that used traditional hand-crafted representation based methods are presented and compared in Table 1 .…”

Section: Hand-crafted Feature Representation For Action Recognitionmentioning

confidence: 99%

A Review on Computer Vision-Based Methods for Human Action Recognition

et al. 2020

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Human action recognition targets recognising different actions from a sequence of observations and different environmental conditions. A wide different applications is applicable to vision based action recognition research. This can include video surveillance, tracking, health care, and human–computer interaction. However, accurate and effective vision based recognition systems continue to be a big challenging area of research in the field of computer vision. This review introduces the most recent human action recognition systems and provides the advances of state-of-the-art methods. To this end, the direction of this research is sorted out from hand-crafted representation based methods including holistic and local representation methods with various sources of data, to a deep learning technology including discriminative and generative models and multi-modality based methods. Next, the most common datasets of human action recognition are presented. This review introduces several analyses, comparisons and recommendations that help to find out the direction of future research.

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“…Approaches to both violence detection and action recognition fall into two categories: traditional, also called handcrafted approaches, and deep learning approaches. A comprehensive view on action recognition, including violence detection, using both handcrafted approaches and deep learning is presented in [12].…”

Section: Related Workmentioning

confidence: 99%

A Sensor Network Approach for Violence Detection in Smart Cities Using Deep Learning

Baba

Gui²,

Cernazanu

et al. 2019

Sensors

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Citizen safety in modern urban environments is an important aspect of life quality. Implementation of a smart city approach to video surveillance depends heavily on the capability of gathering and processing huge amounts of live urban data. Analyzing data from high bandwidth surveillance video streams provided by large size distributed sensor networks is particularly challenging. We propose here an efficient method for automatic violent behavior detection designed for video sensor networks. Known solutions to real-time violence detection are not suitable for implementation in a resource-constrained environment due to the high processing power requirements. Our algorithm achieves real-time processing on a Raspberry PI-embedded architecture. To ensure separation of temporal and spatial information processing we employ a computationally effective cascaded approach. It consists of a deep neural network followed by a time domain classifier. In contrast with current approaches, the deep neural network input is fed exclusively with motion vector features extracted directly from the MPEG encoded video stream. As proven by results, we achieve state-of-the-art performance, while running on a low computational resources embedded architecture.

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A Survey of the Techniques for The Identification and Classification of Human Actions from Visual Data

Cited by 11 publications

References 119 publications

A systematic survey of data mining and big data in human behavior analysis: Current datasets and models

A systematic survey of data mining and big data in human behavior analysis: Current datasets and models

A Review on Computer Vision-Based Methods for Human Action Recognition

A Sensor Network Approach for Violence Detection in Smart Cities Using Deep Learning

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