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Title: | Feature-based annealing particle filter for robust motion capture |
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Author: | López Méndez, Adolfo |
Other authors: | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Casas Pla, Josep Ramon |
Abstract: | This thesis presents a new annealing method for particle filtering aiming at body pose estimation. Particle filters are Monte Carlo methods commonly employed in non-linear and non-Gaussian Bayesian problems, such as the estimation of human dynamics. However, they are ine±cient in high-dimensional state spaces. Annealed particle filter copes with such spaces by introducing a layered stochastic search. Our algorithm aims at generalizing and enhancing the classical annealed particle filter. Diferent image features are exploited in a sequential importance sampling scheme to build better proposal distributions from likelihood. This technique, termed Feature-Based Annealing, is inferred from the required function properties in the annealing process and the properties of the weighting functions obtained with common image features in the field of body tracking. Comparative results between the proposed strategy and common annealed particle filter are shown to assess the robustness of the algorithm. |
Subject(s): | -Àrees temàtiques de la UPC::So, imatge i multimèdia::Creació multimèdia::Imatge digital -Pattern recognition systems -Kalman filtering G -Reconeixement de formes (Informàtica) -Kalman, Filtre de |
Rights: | Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Document type: | Research/Master Thesis |
Published by: | Universitat Politècnica de Catalunya |
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