Gait can be defined as the individuals’ manner of walking. Its analysis can provide significant information about their identity and health, opening a wide range of possibilities in the field of biometric recognition and medical diagnosis. In the field of biometric, the use of gait to perform recognition can provide advantages, such as acquisition from a distance and without the cooperation of the individual being observed. In the field of medicine, gait analysis can be used to detect or assess the development of different gait related pathologies. It can also be used to assess neurological or systemic disorders as their effects are reflected in the individuals’ gait. This Thesis focuses on performing gait analysis in unconstrained environments, using a single 2D camera. This can be a challenging task due to the lack of depth information and self-occlusions in a 2D ...

The field of Life Science Engineering (LSE) is rapidly expanding and predicted to grow strongly in the next decades. It covers areas of food and medical research, plant and pests’ research, and environmental research. In each research area, engineers try to find equations that model a certain life science problem. Once found, they research different numerical techniques to solve for the unknown variables of these equations. Afterwards, solution improvement is examined by adopting more accurate conventional techniques, or developing novel algorithms. In particular, signal and image processing techniques are widely used to solve those LSE problems require pattern recognition. However, due to the continuous evolution of the life science problems and their natures, these solution techniques can not cover all aspects, and therefore demanding further enhancement and improvement. The thesis presents numerical algorithms of digital signal and image processing to ...

The subject of this PhD thesis is the efficient and robust processing and analysis of the audio recordings that are derived from a call center. The thesis is comprised of two parts. The first part is dedicated to dialogue/non-dialogue detection and to speaker segmentation. The systems that are developed are prerequisite for detecting (i) the audio segments that actually contain a dialogue between the system and the call center customer and (ii) the change points between the system and the customer. This way the volume of the audio recordings that need to be processed is significantly reduced, while the system is automated. To detect the presence of a dialogue several systems are developed. This is the first effort found in the international literature that the audio channel is exclusively exploited. Also, it is the first time that the speaker utterance ...

This thesis introduces new learning algorithms for Radial Basis Function (RBF) networks. RBF networks is a feed-forward two-layer neural network used for functional approximation or pattern classification applications. The proposed training algorithms are based on robust statistics. Their theoretical performance has been assessed and compared with that of classical algorithms for training RBF networks. The applications of RBF networks described in this thesis consist of simultaneously modeling moving object segmentation and optical flow estimation in image sequences and 3-D image modeling and segmentation. A Bayesian classifier model is used for the representation of the image sequence and 3-D images. This employs an energy based description of the probability functions involved. The energy functions are represented by RBF networks whose inputs are various features drawn from the images and whose outputs are objects. The hidden units embed kernel functions. Each kernel ...

In the world of Information and communications technology (ICT), strategies for innovation and development are increasingly focusing on applications that require spatial representation and real-time interaction with and within 3D-media environments. One of the major challenges that such applications have to address is user-centricity, reflecting e.g. on developing complexity-hiding services so that people can personalize their own delivery of services. In these terms, multimodal interfaces represent a key factor for enabling an inclusive use of new technologies by everyone. In order to achieve this, multimodal realistic models that describe our environment are needed, and in particular models that accurately describe the acoustics of the environment and communication through the auditory modality are required. Examples of currently active research directions and application areas include 3DTV and future internet, 3D visual-sound scene coding, transmission and reconstruction and teleconferencing systems, to name but ...

The aim of this work is to demonstrate that the human visual modelling yields to effi cient tools dedicated to image processing. The benefi ts are directly related to the human visual system properties and give the ability to solve common major problems encountered in image analysis such as noise reduction, details enhancement, back light correction. We propose a set of low level image processing tools which realize specifi c processing such as contours extraction, spectrum analysis, event detection. These tools are combined in order to create high level image analysis and we propose in this manuscript two examples: a face analyser which extracts eye blinks, yawnings, head motion, this application being applied to hypovigilance detection for drivers. The second considered application concerns general motion analysis and we propose a moving object tracker able to eliminate noise segmentation problems. Finally, ...

This thesis contributes to motion characterization through inertial and physiological signals captured by wearable devices and analyzed using signal processing and deep learning techniques. This research leverages the possibilities of motion analysis for three main applications: to know what physical activity a person is performing (Human Activity Recognition), to identify who is performing that motion (user identification) or know how the movement is being performed (motor anomaly detection). Most previous research has addressed human motion modeling using invasive sensors in contact with the user or intrusive sensors that modify the user’s behavior while performing an action (cameras or microphones). In this sense, wearable devices such as smartphones and smartwatches can collect motion signals from users during their daily lives in a less invasive or intrusive way. Recently, there has been an exponential increase in research focused on inertial-signal processing to ...

The proliferation of handheld devices such as smartphones and tablets brings a new scenario for biometric authentication, and in particular to automatic signature verification. Research on signature verification has been traditionally carried out using signatures acquired on digitizing tablets or Tablet-PCs. This PhD Thesis addresses the problem of user authentication on handled devices using handwritten signatures and graphical passwords based on free-form doodles, as well as the effects of biometric aging on signatures. The Thesis pretends to analyze: (i) which are the effects of mobile conditions on signature and doodle verification, (ii) which are the most distinctive features in mobile conditions, extracted from the pen or fingertip trajectory, (iii) how do different similarity computation (i.e. matching) algorithms behave with signatures and graphical passwords captured on mobile conditions, and (iv) what is the impact of aging on signature features and verification ...

Communicating with mobile devices has become an unavoidable part of our daily life. Unfortunately, the current user interface designs are mostly taken directly from desktop computers. This has resulted in devices that are sometimes hard to use. Since more processing power and new sensing technologies are already available, there is a possibility to develop systems to communicate through different modalities. This thesis proposes some novel computer vision approaches, including head tracking, object motion analysis and device ego-motion estimation, to allow efficient interaction with mobile devices. For head tracking, two new methods have been developed. The first method detects a face region and facial features by employing skin detection, morphology, and a geometrical face model. The second method, designed especially for mobile use, detects the face and eyes using local texture features. In both cases, Kalman filtering is applied to estimate ...

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 ...

As biometrics gains popularity and proliferates into the daily life, there is an increased concern over the loss of privacy and potential misuse of biometric data held in central repositories. The major concerns are about i) the use of biometrics to track people, ii) non-revocability of biometrics (eg. if a fingerprint is compromised it can not be canceled or reissued), and iii) disclosure of sensitive information such as race, gender and health problems which may be revealed by biometric traits. The straightforward suggestion of keeping the biometric data in a user owned token (eg. smart cards) does not completely solve the problem, since malicious users can claim that their token is broken to avoid biometric verification altogether. Put together, these concerns brought the need for privacy preserving biometric authentication methods in the recent years. In this dissertation, we survey existing ...

The level of automation in our society is ever increasing. Technologies like self-driving cars, virtual reality, and fully autonomous robots, which all were unimaginable a few decades ago, are realizable today, and will become standard consumer products in the future. These technologies depend upon autonomous localization and situation awareness where careful processing of sensory data is required. To increase efficiency, robustness and reliability, appropriate models for these data are needed. In this thesis, such models are analyzed within three different application areas, namely (1) magnetic localization, (2) extended target tracking, and (3) autonomous learning from raw pixel information. Magnetic localization is based on one or more magnetometers measuring the induced magnetic field from magnetic objects. In this thesis we present a model for determining the position and the orientation of small magnets with an accuracy of a few millimeters. This ...

The increasing need for personal authentication in many daily applications has made biometrics a fundamental research area. In particular, handwritten signatures have long been considered one of the most valuable biometric traits. Signatures are the most popular method for identity verification all over the world, and people are familiar with the use of signatures for identity verification purposes in their everyday life. In fact, signatures are widely used in several daily transactions, being recognized as a legal means of verifying an individual’s identity by financial and administrative institutions. In addition, signature verification has the advantage of being a non-invasive biometric technique. Two categories of signature verification systems can be distinguished taking into account the acquisition device, namely, offline systems, where only the static image of the signature is available, and online systems, where dynamic information acquired during the signing process, ...

The analysis of audiovisual data aims at extracting high level information, equivalent with the one(s) that can be extracted by a human. It is considered as a fundamental, unsolved (in its general form) problem. Even though the inverse problem, the audiovisual (sound and animation) synthesis, is judged easier than the previous, it remains an unsolved problem. The systematic research on these problems yields solutions that constitute the basis for a great number of continuously developing applications. In this thesis, we examine the two aforementioned fundamental problems. We propose algorithms and models of analysis and synthesis of articulated motion and undulatory (snake) locomotion, using data from video sequences. The goal of this research is the multilevel information extraction from video, like object tracking and activity recognition, and the 3-D animation synthesis in virtual environments based on the results of analysis. An ...

Face recognition has been an active area of study for both computer vision and image processing communities, not only for biometrics but also for human-computer interaction applications. The purpose of the present work is to evaluate the existing 3D face recognition techniques and seek biologically motivated methods to improve them. We especially look at findings in psychophysics and cognitive science for insights. We propose a biologically motivated computational model, and focus on the earlier stages of the model, whose performance is critical for the later stages. Our emphasis is on automatic localization of facial features. We first propose a strong unsupervised learning algorithm for flexible and automatic training of Gaussian mixture models and use it in a novel feature-based algorithm for facial fiducial point localization. We also propose a novel structural correction algorithm to evaluate the quality of landmarking and ...