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Papers by Enrique Cabello

Research paper thumbnail of Scalable and flexible wireless distributed architecture for intelligent video surveillance systems

Multimedia Tools and Applications, 2019

Research paper thumbnail of Face recognition using a permutation coding neural classifier

Neural Computing and Applications, 2015

ABSTRACT

Research paper thumbnail of Real-world human gender classification from oral region using convolutional neural netwrok

Advances in distributed computing and artificial intelligence journal, Jan 24, 2023

Research paper thumbnail of Biometrics in Border Control

Research paper thumbnail of Article Videosensor for the Detection of Unsafe Driving Behavior in the Proximity of Black Spots

Research paper thumbnail of Context-Aware Distance for Anomalous Human Trajectories Detection

In this paper, a novel methodology for the representation and distance measurement of trajectorie... more In this paper, a novel methodology for the representation and distance measurement of trajectories is introduced in order to perform outliers detection tasks. First, a features extraction procedure based on the linear segmentation of trajectories is presented. Next, a configurable context-aware distance is defined. Our representation and distance are significant in that they weigh the relative importance of several relevant features of the trajectories. A clustering method is applied based on the distances matrix and the outliers detection task is performed in any of the clusters. The results of the experiments show the good performance of the method when applied in two different real data sets.

Research paper thumbnail of Lessons learnt in non-supervised record of real crossings

This paper presents an artificial vision based video-sensor designed to detect pedestrian-vehicle... more This paper presents an artificial vision based video-sensor designed to detect pedestrian-vehicle conflicts at crossing points. This video sensor detects moving objects by isolating them from the background. Then the speed and trajectories are estimated using a Kalman filter. Potential conflicts are then predicted. This system has been tested at two real crossing points at the city of Salamanca (Spain).

Research paper thumbnail of Subjective data arrangement using clustering techniques for training expert systems

Expert Systems with Applications, 2019

Research paper thumbnail of 3D facial feature localisation using spin images

Research paper thumbnail of Unsupervised Adaptive Multi-Object Tracking-by-Clustering Algorithm with a Bio-Inspired System

Research paper thumbnail of Combining dynamic finite state machines and text-based similarities to represent human behavior

Engineering Applications of Artificial Intelligence, 2019

Abstract The analysis of human behavior is a popular topic of research since it allows obtaining ... more Abstract The analysis of human behavior is a popular topic of research since it allows obtaining specific information about individuals, their motivations, and the problems and difficulties they can encounter. Human behavior can be grouped to elaborate profiles that would enable the classification of individuals. Nevertheless, the elaboration of profiles related to human behaviors presents some difficulties associated with the volume of data and the number of parameters typically considered. Thus, the development of software able to automatize the manipulation of data through graphical assistants to produce understandable visualizations of the human behaviors is crucial. In this paper, the VISUVER framework is presented. It uses finite state machines to represent and visualize the dynamic human behavior automatically. This behavior could be provided by real data collected by specific sensors or simulated data. The state machines are built in sequential steps in order to illustrate the dynamic evolution of the behavior over time. VISUVER also includes similarity metrics based on text mining techniques to establish possible profiles among the analyzed behaviors. The Intelligent Transportation Systems (ITS) domain has been considered in order to validate the proposal.

Research paper thumbnail of Measuring Driving Quality in Urban Environments

ABSTRACT In this paper, we describe a new framework to detect relevant driving risk variables. Th... more ABSTRACT In this paper, we describe a new framework to detect relevant driving risk variables. The methodology is applied over data sets obtained from a high immersive cabin truck simulator in natural driving conditions. A nonparametric model, based in Nearest Neighbors combined with Restricted Least Squared methods is developed. Three experts were asked to evaluate the driving risk in a truck simulator where the vehicle dynamics factors were stored. Moreover the methodology is extended in order to show the characteristics that they have implicitly selected as the relevant ones.

Research paper thumbnail of Soft-biometrics evaluation for people re-identification in uncontrolled multi-camera environments

EURASIP Journal on Image and Video Processing, 2015

Research paper thumbnail of Driver’s Hand Detection and Tracking Based on Address Event Representation

Lecture Notes in Computational Vision and Biomechanics, 2014

This chapter presents a novel biologically-inspired system capable of detecting and tracking the ... more This chapter presents a novel biologically-inspired system capable of detecting and tracking the hands of the driver during the driving task. The system needs neither marks nor special device in the hands, so a totally natural driving is allowed. Visual information acquisition has been made using an innovative dynamic vision sensor (DVS) that discards the frame concept entirely, encoding the information in the form of Address-Event-Representation (AER) data. This representation allows the information transmission and processing at the same time. An algorithm for detecting and tracking hands using this information in real time is presented. This method has been designed to work with infra-red visual information, avoiding the dependence of the illumination conditions. The proposed system has been integrated in a highly realistic car simulator and several tests have been carried out. Detailed experiments showing the improvement of using AER representation are presented. The presented work is the first approach to introduce AER technology in an automotive environment.

Research paper thumbnail of Videosensor for the Detection of Unsafe Driving Behavior in the Proximity of Black Spots

Research paper thumbnail of Bio-inspired Stereo Vision Calibration for Dynamic Vision Sensors

Research paper thumbnail of Border Control Morphing Attack Detection with a Convolutional Neural Network De-morphing Approach

Research paper thumbnail of Face Presentation Attack Detection using Biologically-inspired Features

Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications

Research paper thumbnail of Optimization of a Face Verification System using Bayesian Screening Techniques

We present a face verification system. A 100 people face database has been created using a CCD vi... more We present a face verification system. A 100 people face database has been created using a CCD video camera, with controlled illumination conditions and frontal upright face position. A Principal Component Analysis matrix has been computed with eight images per person, and only the 150 most important eigenvalues have been used. The results of PCA are fed into two classifiers (SVM and RBF), in order to perform a verification process in a control access. The algorithm proposed here allows to compute automatically the optimal acceptance threshold to divide a population of candidates into genuine or registered and impostors or non-registered. A Bayesian approach based on screening techniques has been considered, so that the user provides the economical cost for false acceptances and false rejections within the system. According to the ratio between these two costs, the optimal acceptance threshold is computed as the value that minimizes the expected total cost for both acceptances and r...

Research paper thumbnail of Técnicas de reconocimiento automático de emociones

Teoría de la Educación: Educación y Cultura en la Sociedad de la Información, 2006

In this paper we present a summary of the main techniques for the automatic recognition of human ... more In this paper we present a summary of the main techniques for the automatic recognition of human emotions. We study the most important kind of emotions, centering on the specific emotions. We focus on the two most relevant ways in which emotions are studied: facial expressions from a video, and phonetic expressions from a speech. Since the type of emotions obtained from these two approaches could be different, the fusion of these different sources of information is one of the most interesting areas of research. We present a review of the statistical techniques used in emotion recognition. A fundamental task is the development of an appropriate database, with real audio-visual data, focus on emotion learning.

Research paper thumbnail of Scalable and flexible wireless distributed architecture for intelligent video surveillance systems

Multimedia Tools and Applications, 2019

Research paper thumbnail of Face recognition using a permutation coding neural classifier

Neural Computing and Applications, 2015

ABSTRACT

Research paper thumbnail of Real-world human gender classification from oral region using convolutional neural netwrok

Advances in distributed computing and artificial intelligence journal, Jan 24, 2023

Research paper thumbnail of Biometrics in Border Control

Research paper thumbnail of Article Videosensor for the Detection of Unsafe Driving Behavior in the Proximity of Black Spots

Research paper thumbnail of Context-Aware Distance for Anomalous Human Trajectories Detection

In this paper, a novel methodology for the representation and distance measurement of trajectorie... more In this paper, a novel methodology for the representation and distance measurement of trajectories is introduced in order to perform outliers detection tasks. First, a features extraction procedure based on the linear segmentation of trajectories is presented. Next, a configurable context-aware distance is defined. Our representation and distance are significant in that they weigh the relative importance of several relevant features of the trajectories. A clustering method is applied based on the distances matrix and the outliers detection task is performed in any of the clusters. The results of the experiments show the good performance of the method when applied in two different real data sets.

Research paper thumbnail of Lessons learnt in non-supervised record of real crossings

This paper presents an artificial vision based video-sensor designed to detect pedestrian-vehicle... more This paper presents an artificial vision based video-sensor designed to detect pedestrian-vehicle conflicts at crossing points. This video sensor detects moving objects by isolating them from the background. Then the speed and trajectories are estimated using a Kalman filter. Potential conflicts are then predicted. This system has been tested at two real crossing points at the city of Salamanca (Spain).

Research paper thumbnail of Subjective data arrangement using clustering techniques for training expert systems

Expert Systems with Applications, 2019

Research paper thumbnail of 3D facial feature localisation using spin images

Research paper thumbnail of Unsupervised Adaptive Multi-Object Tracking-by-Clustering Algorithm with a Bio-Inspired System

Research paper thumbnail of Combining dynamic finite state machines and text-based similarities to represent human behavior

Engineering Applications of Artificial Intelligence, 2019

Abstract The analysis of human behavior is a popular topic of research since it allows obtaining ... more Abstract The analysis of human behavior is a popular topic of research since it allows obtaining specific information about individuals, their motivations, and the problems and difficulties they can encounter. Human behavior can be grouped to elaborate profiles that would enable the classification of individuals. Nevertheless, the elaboration of profiles related to human behaviors presents some difficulties associated with the volume of data and the number of parameters typically considered. Thus, the development of software able to automatize the manipulation of data through graphical assistants to produce understandable visualizations of the human behaviors is crucial. In this paper, the VISUVER framework is presented. It uses finite state machines to represent and visualize the dynamic human behavior automatically. This behavior could be provided by real data collected by specific sensors or simulated data. The state machines are built in sequential steps in order to illustrate the dynamic evolution of the behavior over time. VISUVER also includes similarity metrics based on text mining techniques to establish possible profiles among the analyzed behaviors. The Intelligent Transportation Systems (ITS) domain has been considered in order to validate the proposal.

Research paper thumbnail of Measuring Driving Quality in Urban Environments

ABSTRACT In this paper, we describe a new framework to detect relevant driving risk variables. Th... more ABSTRACT In this paper, we describe a new framework to detect relevant driving risk variables. The methodology is applied over data sets obtained from a high immersive cabin truck simulator in natural driving conditions. A nonparametric model, based in Nearest Neighbors combined with Restricted Least Squared methods is developed. Three experts were asked to evaluate the driving risk in a truck simulator where the vehicle dynamics factors were stored. Moreover the methodology is extended in order to show the characteristics that they have implicitly selected as the relevant ones.

Research paper thumbnail of Soft-biometrics evaluation for people re-identification in uncontrolled multi-camera environments

EURASIP Journal on Image and Video Processing, 2015

Research paper thumbnail of Driver’s Hand Detection and Tracking Based on Address Event Representation

Lecture Notes in Computational Vision and Biomechanics, 2014

This chapter presents a novel biologically-inspired system capable of detecting and tracking the ... more This chapter presents a novel biologically-inspired system capable of detecting and tracking the hands of the driver during the driving task. The system needs neither marks nor special device in the hands, so a totally natural driving is allowed. Visual information acquisition has been made using an innovative dynamic vision sensor (DVS) that discards the frame concept entirely, encoding the information in the form of Address-Event-Representation (AER) data. This representation allows the information transmission and processing at the same time. An algorithm for detecting and tracking hands using this information in real time is presented. This method has been designed to work with infra-red visual information, avoiding the dependence of the illumination conditions. The proposed system has been integrated in a highly realistic car simulator and several tests have been carried out. Detailed experiments showing the improvement of using AER representation are presented. The presented work is the first approach to introduce AER technology in an automotive environment.

Research paper thumbnail of Videosensor for the Detection of Unsafe Driving Behavior in the Proximity of Black Spots

Research paper thumbnail of Bio-inspired Stereo Vision Calibration for Dynamic Vision Sensors

Research paper thumbnail of Border Control Morphing Attack Detection with a Convolutional Neural Network De-morphing Approach

Research paper thumbnail of Face Presentation Attack Detection using Biologically-inspired Features

Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications

Research paper thumbnail of Optimization of a Face Verification System using Bayesian Screening Techniques

We present a face verification system. A 100 people face database has been created using a CCD vi... more We present a face verification system. A 100 people face database has been created using a CCD video camera, with controlled illumination conditions and frontal upright face position. A Principal Component Analysis matrix has been computed with eight images per person, and only the 150 most important eigenvalues have been used. The results of PCA are fed into two classifiers (SVM and RBF), in order to perform a verification process in a control access. The algorithm proposed here allows to compute automatically the optimal acceptance threshold to divide a population of candidates into genuine or registered and impostors or non-registered. A Bayesian approach based on screening techniques has been considered, so that the user provides the economical cost for false acceptances and false rejections within the system. According to the ratio between these two costs, the optimal acceptance threshold is computed as the value that minimizes the expected total cost for both acceptances and r...

Research paper thumbnail of Técnicas de reconocimiento automático de emociones

Teoría de la Educación: Educación y Cultura en la Sociedad de la Información, 2006

In this paper we present a summary of the main techniques for the automatic recognition of human ... more In this paper we present a summary of the main techniques for the automatic recognition of human emotions. We study the most important kind of emotions, centering on the specific emotions. We focus on the two most relevant ways in which emotions are studied: facial expressions from a video, and phonetic expressions from a speech. Since the type of emotions obtained from these two approaches could be different, the fusion of these different sources of information is one of the most interesting areas of research. We present a review of the statistical techniques used in emotion recognition. A fundamental task is the development of an appropriate database, with real audio-visual data, focus on emotion learning.