A Survey on Model Based Approaches for 2D and 3D Visual Human Pose Recovery

Human Pose Recovery has been studied in the field of Computer Vision for the last 40 years. Several approaches have been reported, and significant improvements have been obtained in both data representation and model design. However, the problem of Human Pose Recovery in uncontrolled environments is...

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Main Authors: Xavier Perez-Sala, Sergio Escalera, Cecilio Angulo, Jordi Gonzàlez
Format: Article
Language:English
Published: MDPI AG 2014-03-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/14/3/4189
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spelling doaj-de234b82ba0441c0b33c0d3dff8758092020-11-24T22:00:06ZengMDPI AGSensors1424-82202014-03-011434189421010.3390/s140304189s140304189A Survey on Model Based Approaches for 2D and 3D Visual Human Pose RecoveryXavier Perez-Sala0Sergio Escalera1Cecilio Angulo2Jordi Gonzàlez3Fundació Privada Sant Antoni Abat, Vilanova i la Geltrú, Universitat Politècnica de Catalunya, Vilanova i la Geltrú 08800, Catalonia, SpainDepartment Mathematics (MAIA), Universitat de Barcelona and Computer Vision Center (CVC), Barcelona 08007, Catalonia, SpainAutomatic Control Department (ESAII), Universitat Politècnica de Catalunya, Vilanova i la Geltrú 08800, Catalonia, SpainDepartment Computer Science, Universitat Autònoma de Barcelona and Computer Vision Center (CVC), Bellaterra 08193, Catalonia, SpainHuman Pose Recovery has been studied in the field of Computer Vision for the last 40 years. Several approaches have been reported, and significant improvements have been obtained in both data representation and model design. However, the problem of Human Pose Recovery in uncontrolled environments is far from being solved. In this paper, we define a general taxonomy to group model based approaches for Human Pose Recovery, which is composed of five main modules: appearance, viewpoint, spatial relations, temporal consistence, and behavior. Subsequently, a methodological comparison is performed following the proposed taxonomy, evaluating current SoA approaches in the aforementioned five group categories. As a result of this comparison, we discuss the main advantages and drawbacks of the reviewed literature.http://www.mdpi.com/1424-8220/14/3/4189human pose recoveryhuman body modellingbehavior analysiscomputer vision
collection DOAJ
language English
format Article
sources DOAJ
author Xavier Perez-Sala
Sergio Escalera
Cecilio Angulo
Jordi Gonzàlez
spellingShingle Xavier Perez-Sala
Sergio Escalera
Cecilio Angulo
Jordi Gonzàlez
A Survey on Model Based Approaches for 2D and 3D Visual Human Pose Recovery
Sensors
human pose recovery
human body modelling
behavior analysis
computer vision
author_facet Xavier Perez-Sala
Sergio Escalera
Cecilio Angulo
Jordi Gonzàlez
author_sort Xavier Perez-Sala
title A Survey on Model Based Approaches for 2D and 3D Visual Human Pose Recovery
title_short A Survey on Model Based Approaches for 2D and 3D Visual Human Pose Recovery
title_full A Survey on Model Based Approaches for 2D and 3D Visual Human Pose Recovery
title_fullStr A Survey on Model Based Approaches for 2D and 3D Visual Human Pose Recovery
title_full_unstemmed A Survey on Model Based Approaches for 2D and 3D Visual Human Pose Recovery
title_sort survey on model based approaches for 2d and 3d visual human pose recovery
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2014-03-01
description Human Pose Recovery has been studied in the field of Computer Vision for the last 40 years. Several approaches have been reported, and significant improvements have been obtained in both data representation and model design. However, the problem of Human Pose Recovery in uncontrolled environments is far from being solved. In this paper, we define a general taxonomy to group model based approaches for Human Pose Recovery, which is composed of five main modules: appearance, viewpoint, spatial relations, temporal consistence, and behavior. Subsequently, a methodological comparison is performed following the proposed taxonomy, evaluating current SoA approaches in the aforementioned five group categories. As a result of this comparison, we discuss the main advantages and drawbacks of the reviewed literature.
topic human pose recovery
human body modelling
behavior analysis
computer vision
url http://www.mdpi.com/1424-8220/14/3/4189
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