Interactive 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/74874
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Title: Interactive 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors
Authors: Garcia-Garcia, Alberto | Orts-Escolano, Sergio | Garcia-Rodriguez, Jose | Cazorla, Miguel
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
Keywords: Real-time | GPGPU | RGB-D data | CUDA | Object recognition
Knowledge Area: Arquitectura y Tecnología de Computadores
Issue Date: Mar-2018
Publisher: Springer Berlin Heidelberg
Citation: Journal of Real-Time Image Processing. 2018, 14(3): 585-604. doi:10.1007/s11554-016-0607-x
Abstract: In this work, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: The system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient-assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The resulting system is able to recognize objects in a scene in less than 7 seconds, offering an interactive frame rate and thus allowing its deployment on a mobile robotic platform. Because of that, the system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human–computer interaction systems based on visual information. A video showing the proposed system while performing online object recognition in various scenes is available on our project website (http://www.dtic.ua.es/~agarcia/3dobjrecog-jetsontk1/).
Sponsor: This work was partially funded by the national project SIRMAVED (DPI2013-40534-R).
URI: http://hdl.handle.net/10045/74874
ISSN: 1861-8200 (Print) | 1861-8219 (Online)
DOI: 10.1007/s11554-016-0607-x
Language: eng
Type: info:eu-repo/semantics/article
Rights: © Springer-Verlag Berlin Heidelberg 2016
Peer Review: si
Publisher version: https://doi.org/10.1007/s11554-016-0607-x
Appears in Collections:INV - RoViT - Artículos de Revistas
INV - I2RC - Artículos de Revistas

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