Martinez Berti, E.; Sánchez Salmerón, AJ.; Ricolfe Viala, C. (2017). 4-Dimensional deformation part model for pose estimation using Kalman filter constraints. International Journal of Advanced Robotic Systems. 14(3):1-13. doi:10.1177/1729881417714230
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/102700
Title:
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4-Dimensional deformation part model for pose estimation using Kalman filter constraints
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Author:
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Martínez Bertí, Enrique
Sánchez Salmerón, Antonio José
Ricolfe Viala, Carlos
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UPV Unit:
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Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica
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Issued date:
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Abstract:
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[EN] The goal of this research work is to improve the accuracy of human pose estimation using the deformation part model
without increasing computational complexity. First, the proposed method seeks to improve pose estimation ...[+]
[EN] The goal of this research work is to improve the accuracy of human pose estimation using the deformation part model
without increasing computational complexity. First, the proposed method seeks to improve pose estimation accuracy by
adding the depth channel to deformation part model, which was formerly defined based only on RGB channels, to obtain a
4-dimensional deformation part model. In addition, computational complexity can be controlled by reducing the number
of joints by taking into account in a reduced 4-dimensional deformation part model. Finally, complete solutions are
obtained by solving the omitted joints by using inverse kinematic models. The main goal of this article is to analyze the
effect on pose estimation accuracy when using a Kalman filter added to 4-dimensional deformation part model partial
solutions. The experiments run with two data sets showing that this method improves pose estimation accuracy compared
with state-of-the-art methods and that a Kalman filter helps to increase this accuracy.
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Subjects:
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DPM
,
Kalman filter
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Pose estimation
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Kinematic constraints
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Human activity recognition
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Computer vision
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Motion and tracking
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Copyrigths:
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Reconocimiento (by)
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Source:
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International Journal of Advanced Robotic Systems. (issn:
1729-8806
)
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DOI:
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10.1177/1729881417714230
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Publisher:
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SAGE Publications
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Publisher version:
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http://doi.org/10.1177/1729881417714230
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Project ID:
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MINECO/DPI2013-44227-R
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Thanks:
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The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was partially financed by Plan Nacional de I + D, Comision Interministerial de ...[+]
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was partially financed by Plan Nacional de I + D, Comision Interministerial de Ciencia y Tecnologa (FEDERCICYT) under the project DPI2013-44227-R.
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Type:
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Artículo
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