Toward human activity recognition: a survey

Saleem, Gulshan; Bajwa, Usama Ijaz; Raza, Rana Hammad

doi:10.1007/s00521-022-07937-4

Cited by 62 publications

(16 citation statements)

References 196 publications

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“…To enhance human well-being, a nuanced understanding of daily activities facilitated by advanced HAR technologies such as PoseNet and GHUM is crucial. These models, which utilize convolutional neural networks, have significantly advanced human pose estimation in images and videos, leading to breakthroughs in fields such as smart home systems, elderly care, and physiotherapy [9]- [12].…”

Section: ) Har In Daily Life Actionsmentioning

confidence: 99%

Human Action Recognition Systems: A Review of the Trends and State-of-the-Art

Karim,

Khalid,

Aleryani

et al. 2024

IEEE Access

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Human action recognition (HAR), deeply rooted in computer vision, video surveillance, automated observation, and human computer interaction (HCI), enables precise identification of human actions. Numerous research groups have dedicated their efforts to various applications and problem domains in HAR systems. They trained classification models using diverse datasets, enhanced hardware capabilities, and employed different metrics to assess performance. Although several surveys and review articles have been published periodically to highlight research advancements in HAR, there is currently no comprehensive and up-to-date study that encompasses architecture, application areas, techniques/algorithms, and evaluation methods as well as challenges and issues. To bridge this gap in the literature, this article presents a comprehensive analysis of the current state of HAR systems by thoroughly examining a meticulously chosen collection of 136 publications published within the past two decades. These findings have significant implications for researchers engaged in different aspects of HAR systems.

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Section: ) Har In Daily Life Actionsmentioning

confidence: 99%

Human Action Recognition Systems: A Review of the Trends and State-of-the-Art

Karim,

Khalid,

Aleryani

et al. 2024

IEEE Access

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“…The need for large datasets, effective fusion and co-learning strategies, efficient action analysis, and unsupervised learning techniques has been emphasized. Saleem et al [35] present a comprehensive overview of HAR approaches and trends, proposing a HAR taxonomy and discussing benchmark datasets. They also identify open challenges for future research, including high intra-class variations, inter-class similarities, background variations, and multi-view challenges.…”

Section: Review Of Related Work and Rationale For This Comprehensive ...mentioning

confidence: 99%

Human Action Recognition in Smart Living Services and Applications: Context Awareness, Data Availability, Personalization, and Privacy

Diraco¹,

Rescio²,

Caroppo³

et al. 2023

Preprint

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Smart Living, an increasingly prominent concept, entails incorporating sophisticated technologies in homes and urban environments to elevate the quality of life for citizens. A critical success factor for Smart Living services and applications, from energy management to healthcare and transportation, is the efficacy of human action recognition (HAR). HAR, rooted in computer vision, seeks to identify human actions and activities using visual data and various sensor modalities. This paper extensively reviews the literature on HAR in Smart Living services and applications, amalgamating key contributions and challenges while providing insights into future research directions. The review delves into the essential aspects of Smart Living, the state of the art in HAR, and the potential societal implications of this technology. Moreover, the paper meticulously examines the primary application sectors in Smart Living that stand to gain from HAR, such as smart homes, smart healthcare, and smart cities. By underscoring the significance of the four dimensions of Context Awareness, Data Availability, Personalization, and Privacy in HAR, this paper serves as a valuable resource for researchers and practitioners striving to advance Smart Living services and applications.

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“…The practical applications of HAR are diverse and many and can be discovered in various fields, for instance, healthcare, sports and fitness, human-computer interactions, surveillance and security, and ambient-assisted living. Overall, HAR plays a valuable and essential role in considering human performance, qualifying context-conscious systems, and smoothing relevance that needs automated interpretation and reaction to social activities [6,7].…”

Section: Introductionmentioning

confidence: 99%

Choquet Integral-Based Aczel–Alsina Aggregation Operators for Interval-Valued Intuitionistic Fuzzy Information and Their Application to Human Activity Recognition

et al. 2023

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Human activity recognition (HAR) is the process of interpreting human activities with the help of electronic devices such as computer and machine version technology. Humans can be explained or clarified as gestures, behavior, and activities that are recorded by sensors. In this manuscript, we concentrate on studying the problem of HAR; for this, we use the proposed theory of Aczel and Alsina, such as Aczel–Alsina (AA) norms, and the derived theory of Choquet, such as the Choquet integral in the presence of Atanassov interval-valued intuitionistic fuzzy (AIVIF) set theory for evaluating the novel concept of AIVIF Choquet integral AA averaging (AIVIFC-IAAA), AIVIF Choquet integral AA ordered averaging (AIVIFC-IAAOA), AIVIF Choquet integral AA hybrid averaging (AIVIFC-IAAHA), AIVIF Choquet integral AA geometric (AIVIFC-IAAG), AIVIF Choquet integral AA ordered geometric (AIVIFC-IAAOG), and AIVIF Choquet integral AA hybrid geometric (AIVIFC-IAAHG) operators. Many essential characteristics of the presented techniques are shown, and we also identify their properties with some results. Additionally, we take advantage of the above techniques to produce a technique to evaluate the HAR multiattribute decision-making complications. We derive a functional model for HAR problems to justify the evaluated approaches and to demonstrate their supremacy and practicality. Finally, we conduct a comparison between the proposed and prevailing techniques for the legitimacy of the invented methodologies.

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Toward human activity recognition: a survey

Cited by 62 publications

References 196 publications

Human Action Recognition Systems: A Review of the Trends and State-of-the-Art

Human Action Recognition Systems: A Review of the Trends and State-of-the-Art

Human Action Recognition in Smart Living Services and Applications: Context Awareness, Data Availability, Personalization, and Privacy

Choquet Integral-Based Aczel–Alsina Aggregation Operators for Interval-Valued Intuitionistic Fuzzy Information and Their Application to Human Activity Recognition

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