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4-Dimensional deformation part model for pose estimation using Kalman filter constraints

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4-Dimensional deformation part model for pose estimation using Kalman filter constraints

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dc.contributor.author Martínez Bertí, Enrique es_ES
dc.contributor.author Sánchez Salmerón, Antonio José es_ES
dc.contributor.author Ricolfe Viala, Carlos es_ES
dc.date.accessioned 2018-05-26T04:23:48Z
dc.date.available 2018-05-26T04:23:48Z
dc.date.issued 2017 es_ES
dc.identifier.issn 1729-8806 es_ES
dc.identifier.uri http://hdl.handle.net/10251/102700
dc.description.abstract [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. es_ES
dc.description.sponsorship 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. es_ES
dc.language Inglés es_ES
dc.publisher SAGE Publications es_ES
dc.relation MINECO/DPI2013-44227-R es_ES
dc.relation.ispartof International Journal of Advanced Robotic Systems es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject DPM es_ES
dc.subject Kalman filter es_ES
dc.subject Pose estimation es_ES
dc.subject Kinematic constraints es_ES
dc.subject Human activity recognition es_ES
dc.subject Computer vision es_ES
dc.subject Motion and tracking es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.title 4-Dimensional deformation part model for pose estimation using Kalman filter constraints es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1177/1729881417714230 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation 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 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1177/1729881417714230 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 13 es_ES
dc.type.version info:eu repo/semantics/publishedVersion es_ES
dc.description.volume 14 es_ES
dc.description.issue 3 es_ES
dc.relation.pasarela 362235 es_ES
dc.contributor.funder MINISTERIO DE ECONOMIA INDUSTRIA Y COMPETITIVIDAD es_ES


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