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Serrano-Cuerda J.,Institute Investigacion En Informatica Of Albacete
Electronic Letters on Computer Vision and Image Analysis | Year: 2014

Nowadays, robust human detection is still a key challenge in the field of Computer Vision. Many people detection systems are based on the use of color cameras. Yet, these cameras have problems when the scene is poorly illuminated or when there are sudden lighting changes. This is why, the use of thermal-infrared cameras seems to be an interesting alternative. Indeed, these cameras show a good performance in cold environments. But they offer many troubles in warm scenarios. Under these adverse conditions, human temperature is similar to the thermal readings of the remaining scene elements. This fact makes it hard to distinguish humans from the environment. This PhD thesis develops and implements a robust multisensor [1] human detection system based on fusing the information provided after segmenting infrared [2] and color videos. The final system has been developed based on the INT3-Horus framework [3] recently created in our n&aIS research team [4].


Sladojevic S.,University of Novi Sad | Culibrk D.,University of Novi Sad | Mirkovic M.,University of Novi Sad | Coll D.R.,Institute Investigacion En Informatica Of Albacete | Borba G.R.,Federal Technological University of Parana
Electronic Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013 | Year: 2013

While a fairly large number of databases exist that provide impaired video sequences designed for the development and evaluation of Quality of Experience (QoE) approaches, the impairments due to transmission errors resulting in packet loss in these databases are based on simulation of small number of scenarios and not representative of real transmission scenarios that arise in end-to-end transmission of multimedia to mobile devices. © 2013 IEEE.


Fernandez-Caballero A.,University of Castilla - La Mancha | Lopez M.T.,University of Castilla - La Mancha | Serrano-Cuerda J.,Institute Investigacion En Informatica Of Albacete
Sensors (Basel, Switzerland) | Year: 2014

This paper investigates the robustness of a new thermal-infrared pedestrian detection system under different outdoor environmental conditions. In first place the algorithm for pedestrian ROI extraction in thermal-infrared video based on both thermal and motion information is introduced. Then, the evaluation of the proposal is detailed after describing the complete thermal and motion information fusion. In this sense, the environment chosen for evaluation is described, and the twelve test sequences are specified. For each of the sequences captured from a forward-looking infrared FLIR A-320 camera, the paper explains the weather and light conditions under which it was captured. The results allow us to draw firm conclusions about the conditions under which it can be affirmed that it is efficient to use our thermal-infrared proposal to robustly extract human ROIs.


Ruiz M.C.,University of Castilla - La Mancha | Cazorla D.,University of Castilla - La Mancha | Perez D.,Institute Investigacion En Informatica Of Albacete | Conejero J.,Institute Investigacion En Informatica Of Albacete
Journal of Supercomputing | Year: 2015

The recent appearance, evolution and massive expansion of social media-based technologies, in conjunction with what currently is known as Internet of Things, results in a vertiginous data production. One of the main contributions to address this matter has been the Hadoop framework (which implements the Map/Reduce paradigm), especially when used in conjunction with Cloud computing environments. In this paper, a comprehensive and rigourous study of the Map/Reduce framework using formal methods is presented. Specifically, the Timed Process Algebra BTC is used, and the resulting formal model is evaluated with a real social media data Hadoop-based application. Moreover, the formal model is validated by carrying out several experiments on a real private Cloud environment. Finally, the formal model outcomes are harnessed to determine the best performance–cost agreement in a real scenario. Results show that the proposed model enables to determine in advance both the performance of a Hadoop-based application within Cloud environments and the best performance–cost agreement. © 2015 Springer Science+Business Media New York


Fernandez-Caballero A.,University of Castilla - La Mancha | Fernandez-Caballero A.,Institute Investigacion En Informatica Of Albacete | Lopez M.T.,University of Castilla - La Mancha | Lopez M.T.,Institute Investigacion En Informatica Of Albacete | Serrano-Cuerda J.,Institute Investigacion En Informatica Of Albacete
Sensors (Switzerland) | Year: 2014

This paper investigates the robustness of a new thermal-infrared pedestrian detection system under different outdoor environmental conditions. In first place the algorithm for pedestrian ROI extraction in thermal-infrared video based on both thermal and motion information is introduced. Then, the evaluation of the proposal is detailed after describing the complete thermal and motion information fusion. In this sense, the environment chosen for evaluation is described, and the twelve test sequences are specified. For each of the sequences captured from a forward-looking infrared FLIR A-320 camera, the paper explains the weather and light conditions under which it was captured. The results allow us to draw firm conclusions about the conditions under which it can be affirmed that it is efficient to use our thermal-infrared proposal to robustly extract human ROIs. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

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