Bioinspired point cloud representation: 3D object tracking

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Title: Bioinspired point cloud representation: 3D object tracking
Authors: Orts-Escolano, Sergio | Garcia-Rodriguez, Jose | Cazorla, Miguel | Morell, Vicente | Azorin-Lopez, Jorge | Saval-Calvo, Marcelo | Garcia-Garcia, Alberto | Villena Martínez, Víctor
Research Group/s: Robótica y Visión Tridimensional (RoViT) | Informática Industrial y Redes de Computadores
Center, Department or Service: Universidad de Alicante. Departamento de Tecnología Informática y Computación | Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial
Keywords: Point cloud | 3D | Object representation | Object tracking | Bioinspired representation
Knowledge Area: Arquitectura y Tecnología de Computadores | Ciencia de la Computación e Inteligencia Artificial
Issue Date: May-2018
Publisher: Springer London
Citation: Neural Computing and Applications. 2018, 29(9): 663-672. doi:10.1007/s00521-016-2585-0
Abstract: 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 (
Sponsor: This work was partially funded by the Spanish Government DPI2013-40534-R Grant.
ISSN: 0941-0643 (Print) | 1433-3058 (Online)
DOI: 10.1007/s00521-016-2585-0
Language: eng
Type: info:eu-repo/semantics/article
Rights: © The Natural Computing Applications Forum 2016
Peer Review: si
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