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Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model

In this paper, we propose a new method for spotting and recognizing continuous human actions using a vision sensor. The method is comprised of depth-MHI-HOG (DMH), action modeling, action spotting, and recognition. First, to effectively separate the foreground from background, we propose a method ca...

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Autores principales: Eum, Hyukmin, Yoon, Changyong, Lee, Heejin, Park, Mignon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4435222/
https://www.ncbi.nlm.nih.gov/pubmed/25742172
http://dx.doi.org/10.3390/s150305197
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author Eum, Hyukmin
Yoon, Changyong
Lee, Heejin
Park, Mignon
author_facet Eum, Hyukmin
Yoon, Changyong
Lee, Heejin
Park, Mignon
author_sort Eum, Hyukmin
collection PubMed
description In this paper, we propose a new method for spotting and recognizing continuous human actions using a vision sensor. The method is comprised of depth-MHI-HOG (DMH), action modeling, action spotting, and recognition. First, to effectively separate the foreground from background, we propose a method called DMH. It includes a standard structure for segmenting images and extracting features by using depth information, MHI, and HOG. Second, action modeling is performed to model various actions using extracted features. The modeling of actions is performed by creating sequences of actions through k-means clustering; these sequences constitute HMM input. Third, a method of action spotting is proposed to filter meaningless actions from continuous actions and to identify precise start and end points of actions. By employing the spotter model, the proposed method improves action recognition performance. Finally, the proposed method recognizes actions based on start and end points. We evaluate recognition performance by employing the proposed method to obtain and compare probabilities by applying input sequences in action models and the spotter model. Through various experiments, we demonstrate that the proposed method is efficient for recognizing continuous human actions in real environments.
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spelling pubmed-44352222015-05-19 Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model Eum, Hyukmin Yoon, Changyong Lee, Heejin Park, Mignon Sensors (Basel) Article In this paper, we propose a new method for spotting and recognizing continuous human actions using a vision sensor. The method is comprised of depth-MHI-HOG (DMH), action modeling, action spotting, and recognition. First, to effectively separate the foreground from background, we propose a method called DMH. It includes a standard structure for segmenting images and extracting features by using depth information, MHI, and HOG. Second, action modeling is performed to model various actions using extracted features. The modeling of actions is performed by creating sequences of actions through k-means clustering; these sequences constitute HMM input. Third, a method of action spotting is proposed to filter meaningless actions from continuous actions and to identify precise start and end points of actions. By employing the spotter model, the proposed method improves action recognition performance. Finally, the proposed method recognizes actions based on start and end points. We evaluate recognition performance by employing the proposed method to obtain and compare probabilities by applying input sequences in action models and the spotter model. Through various experiments, we demonstrate that the proposed method is efficient for recognizing continuous human actions in real environments. MDPI 2015-03-03 /pmc/articles/PMC4435222/ /pubmed/25742172 http://dx.doi.org/10.3390/s150305197 Text en © 2015 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 license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Eum, Hyukmin
Yoon, Changyong
Lee, Heejin
Park, Mignon
Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model
title Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model
title_full Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model
title_fullStr Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model
title_full_unstemmed Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model
title_short Continuous Human Action Recognition Using Depth-MHI-HOG and a Spotter Model
title_sort continuous human action recognition using depth-mhi-hog and a spotter model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4435222/
https://www.ncbi.nlm.nih.gov/pubmed/25742172
http://dx.doi.org/10.3390/s150305197
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