Bioinspired point cloud representation: 3D object tracking
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http://hdl.handle.net/10045/74875
Título: | Bioinspired point cloud representation: 3D object tracking |
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Autor/es: | Orts-Escolano, Sergio | Garcia-Rodriguez, Jose | Cazorla, Miguel | Morell, Vicente | Azorin-Lopez, Jorge | Saval-Calvo, Marcelo | Garcia-Garcia, Alberto | Villena Martínez, Víctor |
Grupo/s de investigación o GITE: | Robótica y Visión Tridimensional (RoViT) | Informática Industrial y Redes de Computadores |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Tecnología Informática y Computación | Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial |
Palabras clave: | Point cloud | 3D | Object representation | Object tracking | Bioinspired representation |
Área/s de conocimiento: | Arquitectura y Tecnología de Computadores | Ciencia de la Computación e Inteligencia Artificial |
Fecha de publicación: | may-2018 |
Editor: | Springer London |
Cita bibliográfica: | Neural Computing and Applications. 2018, 29(9): 663-672. doi:10.1007/s00521-016-2585-0 |
Resumen: | The problem of processing point cloud sequences is considered in this work. In particular, a system that represents and tracks objects in dynamic scenes acquired using low-cost sensors such as the Kinect is presented. An efficient neural network-based approach is proposed to represent and estimate the motion of 3D objects. This system addresses multiple computer vision tasks such as object segmentation, representation, motion analysis and tracking. The use of a neural network allows the unsupervised estimation of motion and the representation of objects in the scene. This proposal avoids the problem of finding corresponding features while tracking moving objects. A set of experiments are presented that demonstrate the validity of our method to track 3D objects. Moreover, an optimization strategy is applied to achieve real-time processing rates. Favorable results are presented demonstrating the capabilities of the GNG-based algorithm for this task. Some videos of the proposed system are available on the project website (http://www.dtic.ua.es/~sorts/3d_object_tracking/). |
Patrocinador/es: | This work was partially funded by the Spanish Government DPI2013-40534-R Grant. |
URI: | http://hdl.handle.net/10045/74875 |
ISSN: | 0941-0643 (Print) | 1433-3058 (Online) |
DOI: | 10.1007/s00521-016-2585-0 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © The Natural Computing Applications Forum 2016 |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1007/s00521-016-2585-0 |
Aparece en las colecciones: | INV - RoViT - Artículos de Revistas INV - I2RC - Artículos de Revistas INV - AIA - Artículos de Revistas |
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Archivo | Descripción | Tamaño | Formato | |
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2018_Orts-Escolano_etal_NeuralComput&Applic_final.pdf | Versión final (acceso restringido) | 1,92 MB | Adobe PDF | Abrir Solicitar una copia |
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