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Sensors 2016, 16(4), 493; doi:10.3390/s16040493

Building an Enhanced Vocabulary of the Robot Environment with a Ceiling Pointing Camera

1
Instituto de Investigación en Ingeniería de Aragón, Deptartmento de Informática e Ingeniería de Sistemas, University of Zaragoza, Zaragoza 50018, Spain
2
Centre for Applied Autonomous Sensor Systems, Deptartment of Technology, Örebro University, Örebro SE-70182, Sweden
*
Author to whom correspondence should be addressed.
Academic Editors: João Valente and Antonio Barrientos
Received: 13 November 2015 / Revised: 28 March 2016 / Accepted: 31 March 2016 / Published: 7 April 2016
(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)
View Full-Text   |   Download PDF [14375 KB, uploaded 7 April 2016]   |  

Abstract

Mobile robots are of great help for automatic monitoring tasks in different environments. One of the first tasks that needs to be addressed when creating these kinds of robotic systems is modeling the robot environment. This work proposes a pipeline to build an enhanced visual model of a robot environment indoors. Vision based recognition approaches frequently use quantized feature spaces, commonly known as Bag of Words (BoW) or vocabulary representations. A drawback using standard BoW approaches is that semantic information is not considered as a criteria to create the visual words. To solve this challenging task, this paper studies how to leverage the standard vocabulary construction process to obtain a more meaningful visual vocabulary of the robot work environment using image sequences. We take advantage of spatio-temporal constraints and prior knowledge about the position of the camera. The key contribution of our work is the definition of a new pipeline to create a model of the environment. This pipeline incorporates (1) tracking information to the process of vocabulary construction and (2) geometric cues to the appearance descriptors. Motivated by long term robotic applications, such as the aforementioned monitoring tasks, we focus on a configuration where the robot camera points to the ceiling, which captures more stable regions of the environment. The experimental validation shows how our vocabulary models the environment in more detail than standard vocabulary approaches, without loss of recognition performance. We show different robotic tasks that could benefit of the use of our visual vocabulary approach, such as place recognition or object discovery. For this validation, we use our publicly available data-set. View Full-Text
Keywords: visual vocabulary; computer vision; bag of words; robotics; place recognition; environment description visual vocabulary; computer vision; bag of words; robotics; place recognition; environment description
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Rituerto, A.; Andreasson, H.; Murillo, A.C.; Lilienthal, A.; Guerrero, J.J. Building an Enhanced Vocabulary of the Robot Environment with a Ceiling Pointing Camera. Sensors 2016, 16, 493.

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