Facial Soft Biometrics: Methods, Applications and Solutions

This dissertation studies soft biometrics traits, their applicability in different security and commercial scenarios, as well as related usability aspects. We place the emphasis on human facial soft biometric traits which constitute the set of physical, adhered or behavioral human characteristics that can partially differentiate, classify and identify humans. Such traits, which include characteristics like age, gender, skin and eye color, the presence of glasses, moustache or beard, inherit several advantages such as ease of acquisition, as well as a natural compatibility with how humans perceive their surroundings. Specifically, soft biometric traits are compatible with the human process of classifying and recalling our environment, a process which involves constructions of hierarchical structures of different refined traits. This thesis explores these traits, and their application in soft biometric systems (SBSs), and specifically focuses on how such systems can achieve different goals ...

Dantcheva, Antitza — EURECOM / Telecom ParisTech


Face Recognition Robust to Occlusions

Face recognition is an important technology in computer vision, which often acts as an essential component in biometrics systems, HCI systems, access control systems, multimedia indexing applications, etc. In recent years, identification of subjects in non-controlled scenarios has received large amount of attentions from the biometrics research community. The deployment of real-time and robust face recognition systems can significantly reinforce the safety and security in public places or/and private residences. However, variations due to expressions/illuminations/poses/occlusions can significantly deteriorate the performance of face recognition systems in non-controlled environments. Partial occlusion, which significantly changes the appearance of part of a face, cannot only cause large performance deterioration of face recognition, but also can cause severe security issues. In this thesis, we focus on the occlusion problem in automatic face recognition in noncontrolled environments. Toward this goal, we propose a framework that consists ...

Min, Rui — Telecom ParisTech


Dealing with Variability Factors and Its Application to Biometrics at a Distance

This Thesis is focused on dealing with the variability factors in biometric recognition and applications of biometrics at a distance. In particular, this PhD Thesis explores the problem of variability factors assessment and how to deal with them by the incorporation of soft biometrics information in order to improve person recognition systems working at a distance. The proposed methods supported by experimental results show the benefits of adapting the system considering the variability of the sample at hand. Although being relatively young compared to other mature and long-used security technologies, biometrics have emerged in the last decade as a pushing alternative for applications where automatic recognition of people is needed. Certainly, biometrics are very attractive and useful for video surveillance systems at a distance, widely distributed in our lifes, and for the final user: forget about PINs and passwords, you ...

Tome, Pedro — Universidad Autónoma de Madrid


A Robust Face Recognition Algorithm for Real-World Applications

Face recognition is one of the most challenging problems of computer vision and pattern recognition. The difficulty in face recognition arises mainly from facial appearance variations caused by factors, such as expression, illumination, partial face occlusion, and time gap between training and testing data capture. Moreover, the performance of face recognition algorithms heavily depends on prior facial feature localization step. That is, face images need to be aligned very well before they are fed into a face recognition algorithm, which requires precise facial feature localization. This thesis addresses on solving these two main problems -facial appearance variations due to changes in expression, illumination, occlusion, time gap, and imprecise face alignment due to mislocalized facial features- in order to accomplish its goal of building a generic face recognition algorithm that can function reliably under real-world conditions. The proposed face recognition algorithm ...

Ekenel, Hazim Kemal — University of Karlsruhe


Video Based Detection of Driver Fatigue

This thesis addresses the problem of drowsy driver detection using computer vision techniques applied to the human face. Specifically we explore the possibility of discriminating drowsy from alert video segments using facial expressions automatically extracted from video. Several approaches were previously proposed for the detection and prediction of drowsiness. There has recently been increasing interest in computer vision approaches as it is a potentially promising approach due to its non-invasive nature for detecting drowsiness. Previous studies with vision based approaches detect driver drowsiness primarily by making pre-assumptions about the relevant behavior, focusing on blink rate, eye closure, and yawning. Here we employ machine learning to explore, understand and exploit actual human behavior during drowsiness episodes. We have collected two datasets including facial and head movement measures. Head motion is collected through an accelerometer for the first dataset (UYAN-1) and an ...

Vural, Esra — Sabanci University


Spoofing and Disguise Variations in Face Recognition

Human recognition has become an important topic as the need and investments for security applications grow continuously. Biometrics enable reliable and efficient identity management systems by using physical and behavioral characteristics of the subjects that are permanent, universal and easy to access. This is why, the topic of biometrics attracts higher attention today. Numerous biometric systems exist which utilize various human characteristics. Among all biometrics traits, face recognition is advantageous in terms of accessibility and reliability. It allows identification at relatively high distances for unaware subjects that do not have to cooperate. In this dissertation, two challenges in face recognition are analyzed. The first one is face spoofing. Initially, spoofing in face recognition is explained together with the countermeasure techniques that are proposed for the protection of face recognition systems against spoofing attacks. The second challenge explored in this thesis ...

Kose, Neslihan — EURECOM


Face Recognition's Grand Challenge: uncontrolled conditions under control

The number of cameras increases rapidly in squares, shopping centers, railway stations and airport halls. There are hundreds of cameras in the city center of Amsterdam. This is still modest compared to the tens of thousands of cameras in London, where citizens are expected to be filmed by more than three hundred cameras of over thirty separate Closed Circuit Television (CCTV) systems in a single day [84]. These CCTV systems include both publicly owned systems (railway stations, squares, airports) and privately owned systems (shops, banks, hotels). The main purpose of all these cameras is to detect, prevent and monitor crime and anti-social behaviour. Other goals of camera surveillance can be detection of unauthorized access, improvement of service, fire safety, etc. Since the terrorist attack on 9/11, detection and prevention of terrorist activities especially at high profiled locations such as airports, ...

Boom, Bas — University of Twente


Analysis of electrophysiological measurements during stress monitoring

Work-related musculoskeletal disorders are a growing problem in todays society. These musculoskeletal disorders are caused by, amongst others, repetitive movements and mental stress. Stress is defined as the mismatch between a perceived demand and the perceived capacities to meet this demand. Although stress has a subjective origin, several physiological manifestations (e.g. cardiovascular and muscular) occur during periods of perceived stress. New insight and algorithms to extract information, related to stress are beneficial. Therefore, two series of stress experiments are executed in a laboratory environment, where subjects underwent different tasks inducing physical strain, mental stress and a combination of both. In this manuscript, new and modified algorithms for electromyography signals are presented that improve the individual analysis of electromyography signals. A first algorithm removes the interference of the electrical activity of the heart on singlechannel electromyography measurements. This interference signal is ...

Taelman, Joachim — Katholieke Universiteit Leuven


Heart rate variability : linear and nonlinear analysis with applications in human physiology

Cardiovascular diseases are a growing problem in today’s society. The World Health Organization (WHO) reported that these diseases make up about 30% of total global deaths and that heart diseases have no geographic, gender or socioeconomic boundaries. Therefore, detecting cardiac irregularities early-stage and a correct treatment are very important. However, this requires a good physiological understanding of the cardiovascular system. The heart is stimulated electrically by the brain via the autonomic nervous system, where sympathetic and vagal pathways are always interacting and modulating heart rate. Continuous monitoring of the heart activity is obtained by means of an ElectroCardioGram (ECG). Studying the fluctuations of heart beat intervals over time reveals a lot of information and is called heart rate variability (HRV) analysis. A reduction of HRV has been reported in several cardiological and noncardiological diseases. Moreover, HRV also has a prognostic ...

Vandeput, Steven — KU Leuven


Video person recognition strategies using head motion and facial appearance

In this doctoral dissertation, we principally explore the use of the temporal information available in video sequences for person and gender recognition; in particular, we focus on the analysis of head and facial motion, and their potential application as biometric identifiers. We also investigate how to exploit as much video information as possible for the automatic recognition; more precisely, we examine the possibility of integrating the head and mouth motion information with facial appearance into a multimodal biometric system, and we study the extraction of novel spatio-temporal facial features for recognition. We initially present a person recognition system that exploits the unconstrained head motion information, extracted by tracking a few facial landmarks in the image plane. In particular, we detail how each video sequence is firstly pre-processed by semiautomatically detecting the face, and then automatically tracking the facial landmarks over ...

Matta, Federico — Eurécom / Multimedia communications


Emotion assessment for affective computing based on brain and peripheral signals

Current Human-Machine Interfaces (HMI) lack of “emotional intelligence”, i.e. they are not able to identify human emotional states and take this information into account to decide on the proper actions to execute. The goal of affective computing is to fill this lack by detecting emotional cues occurring during Human-Computer Interaction (HCI) and synthesizing emotional responses. In the last decades, most of the studies on emotion assessment have focused on the analysis of facial expressions and speech to determine the emotional state of a person. Physiological activity also includes emotional information that can be used for emotion assessment but has received less attention despite of its advantages (for instance it can be less easily faked than facial expressions). This thesis reports on the use of two types of physiological activities to assess emotions in the context of affective computing: the activity ...

Chanel, Guillaume — University of Geneva


Detection of epileptic seizures based on video and accelerometer recordings

Epilepsy is one of the most common neurological diseases, especially in children. And although the majority of patients can be treated through medication or surgery (70%-75%), a significant group of patients cannot be treated. For this latter group of patients it is advisable to follow the evolution of the disease. This can be done through a long-term automatic monitoring, which gives an objective measure of the number of seizures that the patient has, for example during the night. On the other hand, there is a reduced social control overnight and the parents or caregivers can miss some seizures. In severe seizures, it is sometimes necessary, however, to avoid dangerous situations during or after the seizure (e.g. the danger of suffocation caused by vomiting or a position that obstructs breathing, or the risk of injury during violent movements), and to comfort ...

Cuppens, Kris — Katholieke Universiteit Leuven


Automatic Analysis of Head and Facial Gestures in Video Streams

Automatic analysis of head gestures and facial expressions is a challenging research area and it has significant applications for intelligent human-computer interfaces. An important task is the automatic classification of non-verbal messages composed of facial signals where both facial expressions and head rotations are observed. This is a challenging task, because there is no definite grammar or code-book for mapping the non-verbal facial signals into a corresponding mental state. Furthermore, non-verbal facial signals and the observed emotions have dependency on personality, society, state of the mood and also the context in which they are displayed or observed. This thesis mainly addresses the three desired tasks for an effective visual information based automatic face and head gesture (FHG) analyzer. First we develop a fully automatic, robust and accurate 17-point facial landmark localizer based on local appearance information and structural information of ...

Cinar Akakin, Hatice — Bogazici University


Decision threshold estimation and model quality evaluation techniques for speaker verification

The number of biometric applications has increased a lot in the last few years. In this context, the automatic person recognition by some physical traits like fingerprints, face, voice or iris, plays an important role. Users demand this type of applications every time more and the technology seems already mature. People look for security, low cost and accuracy but, at the same time, there are many other factors in connection with biometric applications that are growing in importance. Intrusiveness is undoubtedly a burning factor to decide about the biometrics we will used for our application. At this point, one can realize about the suitability of speaker recognition because voice is the natural way of communicating, can be remotely used and provides a low cost. Automatic speaker recognition is commonly used in telephonic applications although it can also be used in ...

Rodriguez Saeta, Javier — Universitat Politecnica de Catalunya


Affective Signal Processing (ASP): Unraveling the mystery of emotions

Slowly computers are being dressed and becoming huggable and tangible. They are being personalized and are expected to understand more of their users' feelings, emotions, and moods: This we refer to as affective computing. The work and experiences from 50+ publications on affective computing is collected and reported in one concise monograph. A brief introduction on emotion theory and affective computing is given and its relevance for computer science (i.e., Human-Computer Interaction, Artificial Intelligence (AI), and Health Informatics) is denoted. Next, a closed model for affective computing is introduced and reviews of both biosignals and affective computing are presented. The conclusion of all of this is that affective computing lacks standards. Affective computing's key dimensions need to be identified and studied to bring the field the progress it needs. A series of studies is presented that explore baseline-free affective computing, ...

van den Broek, Egon L. — University of Twente

The current layout is optimized for mobile phones. Page previews, thumbnails, and full abstracts will remain hidden until the browser window grows in width.

The current layout is optimized for tablet devices. Page previews and some thumbnails will remain hidden until the browser window grows in width.