Cargando…
A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views
This paper presents a novel silhouette-based feature for vision-based human action recognition, which relies on the contour of the silhouette and a radial scheme. Its low-dimensionality and ease of extraction result in an outstanding proficiency for real-time scenarios. This feature is used in a lea...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4897265/ https://www.ncbi.nlm.nih.gov/pubmed/27379310 http://dx.doi.org/10.1155/2014/547069 |
_version_ | 1782436121403195392 |
---|---|
author | Chaaraoui, Alexandros Andre Flórez-Revuelta, Francisco |
author_facet | Chaaraoui, Alexandros Andre Flórez-Revuelta, Francisco |
author_sort | Chaaraoui, Alexandros Andre |
collection | PubMed |
description | This paper presents a novel silhouette-based feature for vision-based human action recognition, which relies on the contour of the silhouette and a radial scheme. Its low-dimensionality and ease of extraction result in an outstanding proficiency for real-time scenarios. This feature is used in a learning algorithm that by means of model fusion of multiple camera streams builds a bag of key poses, which serves as a dictionary of known poses and allows converting the training sequences into sequences of key poses. These are used in order to perform action recognition by means of a sequence matching algorithm. Experimentation on three different datasets returns high and stable recognition rates. To the best of our knowledge, this paper presents the highest results so far on the MuHAVi-MAS dataset. Real-time suitability is given, since the method easily performs above video frequency. Therefore, the related requirements that applications as ambient-assisted living services impose are successfully fulfilled. |
format | Online Article Text |
id | pubmed-4897265 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-48972652016-07-04 A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views Chaaraoui, Alexandros Andre Flórez-Revuelta, Francisco Int Sch Res Notices Research Article This paper presents a novel silhouette-based feature for vision-based human action recognition, which relies on the contour of the silhouette and a radial scheme. Its low-dimensionality and ease of extraction result in an outstanding proficiency for real-time scenarios. This feature is used in a learning algorithm that by means of model fusion of multiple camera streams builds a bag of key poses, which serves as a dictionary of known poses and allows converting the training sequences into sequences of key poses. These are used in order to perform action recognition by means of a sequence matching algorithm. Experimentation on three different datasets returns high and stable recognition rates. To the best of our knowledge, this paper presents the highest results so far on the MuHAVi-MAS dataset. Real-time suitability is given, since the method easily performs above video frequency. Therefore, the related requirements that applications as ambient-assisted living services impose are successfully fulfilled. Hindawi Publishing Corporation 2014-10-29 /pmc/articles/PMC4897265/ /pubmed/27379310 http://dx.doi.org/10.1155/2014/547069 Text en Copyright © 2014 A. A. Chaaraoui and F. Flórez-Revuelta. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Chaaraoui, Alexandros Andre Flórez-Revuelta, Francisco A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views |
title | A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views |
title_full | A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views |
title_fullStr | A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views |
title_full_unstemmed | A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views |
title_short | A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views |
title_sort | low-dimensional radial silhouette-based feature for fast human action recognition fusing multiple views |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4897265/ https://www.ncbi.nlm.nih.gov/pubmed/27379310 http://dx.doi.org/10.1155/2014/547069 |
work_keys_str_mv | AT chaaraouialexandrosandre alowdimensionalradialsilhouettebasedfeatureforfasthumanactionrecognitionfusingmultipleviews AT florezrevueltafrancisco alowdimensionalradialsilhouettebasedfeatureforfasthumanactionrecognitionfusingmultipleviews AT chaaraouialexandrosandre lowdimensionalradialsilhouettebasedfeatureforfasthumanactionrecognitionfusingmultipleviews AT florezrevueltafrancisco lowdimensionalradialsilhouettebasedfeatureforfasthumanactionrecognitionfusingmultipleviews |