3D object detection with deep learning

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/67916
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Title: 3D object detection with deep learning
Authors: Escalona, Félix | Rodríguez, Ángel | Gomez-Donoso, Francisco | Martínez-Gómez, Jesús | Cazorla, Miguel
Research Group/s: Robótica y Visión Tridimensional (RoViT)
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial
Keywords: Semantic mapping | 3D point cloud | Deep learning
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial
Issue Date: Jul-2017
Publisher: Red de Agentes Físicos
Citation: Journal of Physical Agents. 2017, 8(1): 3-10. doi:10.14198/JoPha.2017.8.1.02
Abstract: Finding an appropriate environment representation is a crucial problem in robotics. 3D data has been recently used thanks to the advent of low cost RGB-D cameras. We propose a new way to represent a 3D map based on the information provided by an expert. Namely, the expert is the output of a Convolutional Neural Network trained with deep learning techniques. Relying on such information, we propose the generation of 3D maps using individual semantic labels, which are associated with environment objects or semantic labels. So, for each label we are provided with a partial 3D map whose data belong to the 3D perceptions, namely point clouds, which have an associated probability above a given threshold. The final map is obtained by registering and merging all these partial maps. The use of semantic labels provide us a with way to build the map while recognizing objects.
Sponsor: This work has been supported by the Spanish Government TIN2016-76515-R Grant, supported with Feder funds, and by grant of Vicerrectorado de Investigación y Transferencia de Conocimiento para el fomento de la I+D+i en la Universidad de Alicante 2016.
URI: http://dx.doi.org/10.14198/JoPha.2017.8.1.02 | http://hdl.handle.net/10045/67916
ISSN: 1888-0258
DOI: 10.14198/JoPha.2017.8.1.02
Language: eng
Type: info:eu-repo/semantics/article
Rights: Creative Commons License Attribution-ShareAlike 4.0
Peer Review: si
Publisher version: http://www.jopha.ua.es/
Appears in Collections:Journal of Physical Agents - 2017, Vol. 8, No. 1
INV - RoViT - Artículos de Revistas

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