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Video Activity Recognition: State-of-the-Art
Video activity recognition, although being an emerging task, has been the subject of important research efforts due to the importance of its everyday applications. Surveillance by video cameras could benefit greatly by advances in this field. In the area of robotics, the tasks of autonomous navigati...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679256/ https://www.ncbi.nlm.nih.gov/pubmed/31323804 http://dx.doi.org/10.3390/s19143160 |
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author | Rodríguez-Moreno, Itsaso Martínez-Otzeta, José María Sierra, Basilio Rodriguez, Igor Jauregi, Ekaitz |
author_facet | Rodríguez-Moreno, Itsaso Martínez-Otzeta, José María Sierra, Basilio Rodriguez, Igor Jauregi, Ekaitz |
author_sort | Rodríguez-Moreno, Itsaso |
collection | PubMed |
description | Video activity recognition, although being an emerging task, has been the subject of important research efforts due to the importance of its everyday applications. Surveillance by video cameras could benefit greatly by advances in this field. In the area of robotics, the tasks of autonomous navigation or social interaction could also take advantage of the knowledge extracted from live video recording. The aim of this paper is to survey the state-of-the-art techniques for video activity recognition while at the same time mentioning other techniques used for the same task that the research community has known for several years. For each of the analyzed methods, its contribution over previous works and the proposed approach performance are discussed. |
format | Online Article Text |
id | pubmed-6679256 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66792562019-08-19 Video Activity Recognition: State-of-the-Art Rodríguez-Moreno, Itsaso Martínez-Otzeta, José María Sierra, Basilio Rodriguez, Igor Jauregi, Ekaitz Sensors (Basel) Review Video activity recognition, although being an emerging task, has been the subject of important research efforts due to the importance of its everyday applications. Surveillance by video cameras could benefit greatly by advances in this field. In the area of robotics, the tasks of autonomous navigation or social interaction could also take advantage of the knowledge extracted from live video recording. The aim of this paper is to survey the state-of-the-art techniques for video activity recognition while at the same time mentioning other techniques used for the same task that the research community has known for several years. For each of the analyzed methods, its contribution over previous works and the proposed approach performance are discussed. MDPI 2019-07-18 /pmc/articles/PMC6679256/ /pubmed/31323804 http://dx.doi.org/10.3390/s19143160 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Rodríguez-Moreno, Itsaso Martínez-Otzeta, José María Sierra, Basilio Rodriguez, Igor Jauregi, Ekaitz Video Activity Recognition: State-of-the-Art |
title | Video Activity Recognition: State-of-the-Art |
title_full | Video Activity Recognition: State-of-the-Art |
title_fullStr | Video Activity Recognition: State-of-the-Art |
title_full_unstemmed | Video Activity Recognition: State-of-the-Art |
title_short | Video Activity Recognition: State-of-the-Art |
title_sort | video activity recognition: state-of-the-art |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679256/ https://www.ncbi.nlm.nih.gov/pubmed/31323804 http://dx.doi.org/10.3390/s19143160 |
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