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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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 |
work_keys_str_mv |
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