Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities
<p dir="ltr">Human action recognition systems use data collected from a wide range of sensors to accurately identify and interpret human actions. One of the most challenging issues for computer vision is the automatic and precise identification of human activities. A significant incr...
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2023
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| _version_ | 1864513508076421120 |
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| author | Md Golam Morshed (19420537) |
| author2 | Tangina Sultana (19420540) Aftab Alam (5158601) Young-Koo Lee (19420543) |
| author2_role | author author author |
| author_facet | Md Golam Morshed (19420537) Tangina Sultana (19420540) Aftab Alam (5158601) Young-Koo Lee (19420543) |
| author_role | author |
| dc.creator.none.fl_str_mv | Md Golam Morshed (19420537) Tangina Sultana (19420540) Aftab Alam (5158601) Young-Koo Lee (19420543) |
| dc.date.none.fl_str_mv | 2023-02-15T09:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3390/s23042182 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Human_Action_Recognition_A_Taxonomy-Based_Survey_Updates_and_Opportunities/26661559 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Artificial intelligence Computer vision and multimedia computation Human-centred computing Machine learning human action recognition computer vision deep learning hand-crafted taxonomy survey |
| dc.title.none.fl_str_mv | Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Human action recognition systems use data collected from a wide range of sensors to accurately identify and interpret human actions. One of the most challenging issues for computer vision is the automatic and precise identification of human activities. A significant increase in feature learning-based representations for action recognition has emerged in recent years, due to the widespread use of deep learning-based features. This study presents an in-depth analysis of human activity recognition that investigates recent developments in computer vision. Augmented reality, human–computer interaction, cybersecurity, home monitoring, and surveillance cameras are all examples of computer vision applications that often go in conjunction with human action detection. We give a taxonomy-based, rigorous study of human activity recognition techniques, discussing the best ways to acquire human action features, derived using RGB and depth data, as well as the latest research on deep learning and hand-crafted techniques. We also explain a generic architecture to recognize human actions in the real world and its current prominent research topic. At long last, we are able to offer some study analysis concepts and proposals for academics. In-depth researchers of human action recognition will find this review an effective tool.</p><h2>Other Information</h2><p dir="ltr">Published in: Sensors<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/s23042182" target="_blank">https://dx.doi.org/10.3390/s23042182</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_e5c6dcc1b74a8b0ef145058705cae838 |
| identifier_str_mv | 10.3390/s23042182 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/26661559 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Human Action Recognition: A Taxonomy-Based Survey, Updates, and OpportunitiesMd Golam Morshed (19420537)Tangina Sultana (19420540)Aftab Alam (5158601)Young-Koo Lee (19420543)Information and computing sciencesArtificial intelligenceComputer vision and multimedia computationHuman-centred computingMachine learninghuman action recognitioncomputer visiondeep learninghand-craftedtaxonomysurvey<p dir="ltr">Human action recognition systems use data collected from a wide range of sensors to accurately identify and interpret human actions. One of the most challenging issues for computer vision is the automatic and precise identification of human activities. A significant increase in feature learning-based representations for action recognition has emerged in recent years, due to the widespread use of deep learning-based features. This study presents an in-depth analysis of human activity recognition that investigates recent developments in computer vision. Augmented reality, human–computer interaction, cybersecurity, home monitoring, and surveillance cameras are all examples of computer vision applications that often go in conjunction with human action detection. We give a taxonomy-based, rigorous study of human activity recognition techniques, discussing the best ways to acquire human action features, derived using RGB and depth data, as well as the latest research on deep learning and hand-crafted techniques. We also explain a generic architecture to recognize human actions in the real world and its current prominent research topic. At long last, we are able to offer some study analysis concepts and proposals for academics. In-depth researchers of human action recognition will find this review an effective tool.</p><h2>Other Information</h2><p dir="ltr">Published in: Sensors<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/s23042182" target="_blank">https://dx.doi.org/10.3390/s23042182</a></p>2023-02-15T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3390/s23042182https://figshare.com/articles/journal_contribution/Human_Action_Recognition_A_Taxonomy-Based_Survey_Updates_and_Opportunities/26661559CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/266615592023-02-15T09:00:00Z |
| spellingShingle | Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities Md Golam Morshed (19420537) Information and computing sciences Artificial intelligence Computer vision and multimedia computation Human-centred computing Machine learning human action recognition computer vision deep learning hand-crafted taxonomy survey |
| status_str | publishedVersion |
| title | Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities |
| title_full | Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities |
| title_fullStr | Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities |
| title_full_unstemmed | Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities |
| title_short | Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities |
| title_sort | Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities |
| topic | Information and computing sciences Artificial intelligence Computer vision and multimedia computation Human-centred computing Machine learning human action recognition computer vision deep learning hand-crafted taxonomy survey |