Por favor, use este identificador para citar o enlazar este ítem: https://repositorio.cetys.mx/handle/60000/120
Título : Pose Estimation in Noncontinuous Video Sequences Using Evolutionary Correlation Filtering
Otros títulos : Hindawi. Mathematical Problems in Engineering
Autor : Picos, Kenia
Orozco Rosas, Ulises
Díaz-Ramírez, Víctor H.
Montiel, Oscar
Palabras clave : Noncontinuous Video Sequences;Evolutionary Correlation Filtering
Fecha de publicación : 31-oct-2018
Citación : 2018;
Resumen : In this paper, we propose an evolutionary correlation fltering approach for solving pose estimation in noncontinuous video sequences. Te proposed algorithm computes the linear correlation between the input scene containing a target in an unknown environment and a bank of matched flters constructed from multiple views of the target and estimates of statistical parameters of the scene. An evolutionary approach for fnding the optimal flter that produces the highest matching score in the correlator is implemented. Te parameters of the flter bank evolve through generations to refne the quality of pose estimation. Te obtained results demonstrate the robustness of the proposed algorithm in challenging image conditions such as noise, cluttered background, abrupt pose changes, and motion blur. Te performance of the proposed algorithm yields high accuracy in terms of objective metrics for pose estimation in noncontinuous video sequences.
metadata.dc.description.url: https://doi.org/10.1155/2018/5798696
URI : https://repositorio.cetys.mx/handle/60000/120
ISSN : 1563-5147
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