Dr. Francisco Florez-Revuelta
Universidad de Alicante
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Academic Career Length
29Years (1998-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications1 June 2015 in Expert Systems with Applications
Journal Article
JPJosé Ramón Padilla-López
José Ramón Padilla-López
ACAlexandros Andre Chaaraoui
Alexandros Andre Chaaraoui
Francisco Florez-Revuelta1 September 2012 in Expert Systems with Applications
Journal Article
ACAlexandros André Chaaraoui
Alexandros André ChaaraouiPCPau Climent-Pérez
Pau Climent-PérezFrancisco Florez-RevueltaHuman Behaviour Analysis (HBA) is more and more being of interest for computer vision and artificial intelligence researchers. Its main application areas, like Video Surveillance and Ambient-Assisted Living (AAL), have been in great demand in recent years. This paper provides a review on HBA for AAL and ageing in place purposes focusing specially on vision techniques. First, a clearly defined taxonomy is presented in order to classify the reviewed works, which are consequently presented following a bottom-up abstraction and complexity order. At the motion level, pose and gaze estimation as well as basic human movement recognition are covered. Next, the mainly used action and activity recognition approaches are presented with examples of recent research works. Increasing the degree of semantics and the time interval involved in the HBA, finally the behaviour level is reached. Furthermore, useful tools and datasets are analysed in order to provide help for initiating projects.This work has been partially supported by the Spanish Ministry of Science and Innovation under project “Sistema de visión para la monitorización de la actividad de la vida diaria en el hogar” (TIN2010-20510-C04-02). Alexandros Andre Chaaraoui acknowledges financial support by the Conselleria d’Educació, Formació i Ocupació of the Generalitat Valenciana (fellowship ACIF/2011/160)
1 November 2013 in Pattern Recognition Letters
Journal Article
ACAlexandros Andre Chaaraoui
Alexandros Andre ChaaraouiPCPau Climent-Pérez
Pau Climent-PérezFrancisco Florez-RevueltaIn this paper, a human action recognition method is presented in which pose representation is based on the contour points of the human silhouette and actions are learned by making use of sequences of multi-view key poses. Our contribution is twofold. Firstly, our approach achieves state-of-the-art success rates without compromising the speed of the recognition process and therefore showing suitability for online recognition and real-time scenarios. Secondly, dissimilarities among different actors performing the same action are handled by taking into account variations in shape (shifting the test data to the known domain of key poses) and speed (considering inconsistent time scales in the classification). Experimental results on the publicly available Weizmann, MuHAVi and IXMAS datasets return high and stable success rates, achieving, to the best of our knowledge, the best rate so far on the MuHAVi Novel Actor test.This work has been partially supported by the Spanish Ministry of Science and Innovation under project “Sistema de visión para la monitorización de la actividad de la vida diaria en el hogar” (TIN2010-20510-C04-02) and by the European Commission under project “caring4U – A study on people activity in private spaces: towards a multisensor network that meets privacy requirements” (PIEF-GA-2010–274649). Alexandros Andre Chaaraoui acknowledges financial support by the Conselleria d’Educació, Formació i Ocupació of the Generalitat Valenciana (fellowship ACIF/2011/160)
Journal Article
Ivan Miguel Pires
Nuno M. GarciaNPNuno Pombo
Nuno PomboFrancisco Florez-RevueltaThis paper focuses on the research on the state of the art for sensor fusion techniques, applied to the sensors embedded in mobile devices, as a means to help identify the mobile device user’s daily activities. Sensor data fusion techniques are used to consolidate the data collected from several sensors, increasing the reliability of the algorithms for the identification of the different activities. However, mobile devices have several constraints, e.g., low memory, low battery life and low processing power, and some data fusion techniques are not suited to this scenario. The main purpose of this paper is to present an overview of the state of the art to identify examples of sensor data fusion techniques that can be applied to the sensors available in mobile devices aiming to identify activities of daily living (ADLs).
1 February 2014 in Expert Systems with Applications
Journal Article
ACAlexandros Andre Chaaraoui
Alexandros Andre ChaaraouiJPJosé Ramón Padilla-López
José Ramón Padilla-López
PCPau Climent-Pérez
Pau Climent-PérezFrancisco Florez-RevueltaInterest in RGB-D devices is increasing due to their low price and the wide range of possible applications that come along. These devices provide a marker-less body pose estimation by means of skeletal data consisting of 3D positions of body joints. These can be further used for pose, gesture or action recognition. In this work, an evolutionary algorithm is used to determine the optimal subset of skeleton joints, taking into account the topological structure of the skeleton, in order to improve the final success rate. The proposed method has been validated using a state-of-the-art RGB action recognition approach, and applying it to the MSR-Action3D dataset. Results show that the proposed algorithm is able to significantly improve the initial recognition rate and to yield similar or better success rates than the state-of-the-art methods.This work has been partially supported by the European Commission under project “caring4U – A study on people activity in private spaces: towards a multisensor network that meets privacy requirements” (PIEF-GA-2010-274649) and by the Spanish Ministry of Science and Innovation under project “Sistema de visión para la monitorización de la actividad de la vida diaria en el hogar” (TIN2010-20510-C04-02). Alexandros Andre Chaaraoui and José Ramón Padilla-López acknowledge financial support by the Conselleria d’Educació, Formació i Ocupació of the Generalitat Valenciana (fellowships ACIF/2011/160 and ACIF/2012/064 respectively)
Journal Article
Ivan Miguel PiresGMGonçalo Marques
Gonçalo MarquesNuno M. GarciaFrancisco Florez-Revuelta
Vasco PoncianoSOSalome Oniani
Salome OnianiMobile health applications are applied for different purposes. Healthcare professionals and other users can use this type of mobile applications for specific tasks, such as diagnosis, information, prevention, treatment, and communication. This paper presents an analysis of mobile health applications used by healthcare professionals and their patients. A secondary objective of this article is to evaluate the scientific validation of these mobile health applications and to verify if the results provided by these applications have an underlying sound scientific foundation. This study also analyzed literature references and the use of mobile health applications available in online application stores. In general, a large part of these mobile health applications provides information about scientific validation. However, some mobile health applications are not validated. Therefore, the main contribution of this paper is to provide a comprehensive analysis of the usability and user-perceived quality of mobile health applications and the challenges related to scientific validation of these mobile applications.
About Me
I am an Associate Professor at the Department of Computer Technology, University of Alicante (Spain) where I belong to the Domotics and Ambient Intelligence research group and the University Institute for Computer Research.
My main research work is focused on ambient assisted living: person-environment interaction, computer vision, and support to the activities of daily living of elderly and/or disabled people. This is the area of application of my whole research background: computational intelligence (neural networks, evolutionary computation), computer vision, home automation, and assistive technologies.
Between 2011 and 2016, I had several positions (Marie Curie fellow, and Senior Researcher) at Kingston University, where I led the Theme on Technologies for Active and Assisted Living in the Interdisciplinary Hub for the Study of Health and Age-related conditions (IhSHA). I was also a member of the Digital Information Research Centre.
I am currently the coordinator of PAAL - Privacy-Aware and Acceptable Lifelogging services for older and frail people, funded under the framework of the transnational Joint Programming Initiative "More Years, Better Lives", and visuAAL - Privacy-Aware and Acceptable Video-Based Technologies and Services for Active and Assisted Living, a Marie Sklodowska-Curie Innovative Training Network. I am the Chair of the GoodBrother COST Action - International Network on Privacy-Aware Audio- and Video-Based Applications for Active and Assisted Living.