Depth-based face recognition using local quantized patterns adapted for range data

A depth-based face recognition algorithm specially adapted to high range resolution data acquired by the new Microsoft Kinect 2 sensor is presented. A novel descriptor called Depth Local Quantized Pattern descriptor has been designed to make use of the extended range resolution of the new sensor. This descriptor is a substantial modification of the popular Local Binary Pattern algorithm. One of the main contributions is the introduction of a quantification step, increasing its capacity to distinguish different depth patterns. The proposed descriptor has been used to train and test a Support Vector Machine classifier, which has proven to be able to accurately recognize different people faces from a wide range of poses. In addition, a new depth-based face database acquired by the new Kinect 2 sensor have been created and made public to evaluate the proposed face recognition system.

Super-resolution Properties of the Maxwell Fish-Eyes

In this paper we present an analysis that shows the Maxwell Fish Eye (MFE) only has super-resolution property for some particular frequencies (for other frequencies, the MFE behaves as conventional imaging lens). These frequencies are directly connected with the Schumann resonance frequencies of spherical symmetric systems. The analysis have been done using a thin spherical waveguide (two concentric spheres with constant index between them), which is a dual form of the MFE (the electrical fields in the MFE can be mapped into the radial electrical fields in the spherical waveguide). In the spherical waveguide the fields are guided inside the space between the concentric spheres. A microwave circuit comprising three elements: the spherical waveguide, the source and the receiver (two coaxial cables) is designed in COMSOL. The super-resolution is demonstrated by calculation of Scaterring (S) parameters for different position of the coaxial cables and different frequencies of the input signal.

Super-Resolution in Respiratory Synchronized Positron Emission Tomography

Respiratory motion is a major source of reduced quality in positron emission tomography (PET). In order to minimize its effects, the use of respiratory synchronized acquisitions, leading to gated frames, has been suggested. Such frames, however, are of low signal-to-noise ratio (SNR) as they contain reduced statistics. Super-resolution (SR) techniques make use of the motion in a sequence of images in order to improve their quality. They aim at enhancing a low-resolution image belonging to a sequence of images representing different views of the same scene. In this work, a maximum a posteriori (MAP) super-resolution algorithm has been implemented and applied to respiratory gated PET images for motion compensation. An edge preserving Huber regularization term was used to ensure convergence. Motion fields were recovered using a B-spline based elastic registration algorithm. The performance of the SR algorithm was evaluated through the use of both simulated and clinical datasets by assessing image SNR, as well as the contrast, position and extent of the different lesions. Results were compared to summing the registered synchronized frames on both simulated and clinical datasets. The super-resolution image had higher SNR (by a factor of over 4 on average) and lesion contrast (by a factor of 2) than the single respiratory synchronized frame using the same reconstruction matrix size. In comparison to the motion corrected or the motion free images a similar SNR was obtained, while improvements of up to 20% in the recovered lesion size and contrast were measured. Finally, the recovered lesion locations on the SR images were systematically closer to the true simulated lesion positions. These observations concerning the SNR, lesion contrast and size were confirmed on two clinical datasets included in the study. In conclusion, the use of SR techniques applied to respiratory motion synchronized images lead to motion compensation combined with improved image SNR and contrast, without any increase in the overall acquisition times.

Super-resolution for a point source using positive refraction

Leonhardt demonstrated (2009) that the 2D Maxwell Fish Eye lens (MFE) can focus perfectly 2D Helmholtz waves of arbitrary frequency, i.e., it can transport perfectly an outward (monopole) 2D Helmholtz wave field, generated by a point source, towards a receptor called "perfect drain" (PD) located at the corresponding MFE image point. The PD has the property of absorbing the complete radiation without radiation or scattering and it has been claimed as necessary to obtain super-resolution (SR) in the MFE. However, a prototype using a "drain" different from the PD has shown λ/5 resolution for microwave frequencies (Ma et al, 2010). Recently, the SR properties of a device equivalent to the MFE, called the Spherical Geodesic Waveguide (SGW) (Miñano et al, 2012) have been analyzed. The reported results show resolution up to λ /3000, for the SGW loaded with the perfect drain, and up to λ /500 f for the SGW without perfect drain. The perfect drain was realized as a coaxial probe loaded with properly calculated impedance. The SGW provides SR only in a narrow band of frequencies close to the resonance Schumann frequencies. Here we analyze the SGW loaded with a small "perfect drain region" (González et al, 2011). This drain is designed as a region made of a material with complex permittivity. The comparative results show that there is no significant difference in the SR properties for both perfect drain designs.

COMSOL Multyphisics Super Resolution Analysis of a Spherical Geodesic Waveguide Suitable for Manufacturing

Recently it has been proved theoretically (Miñano et al, 2011) that the super-resolution up to ?/500 can be achieved using an ideal metallic Spherical Geodesic Waveguide (SGW). This SGW is a theoretical design, in which the conductive walls are considered to be lossless conductors with zero thickness. In this paper, we study some key parameters that might influence the super resolution properties reported in (Miñano et al, 2011), such as losses, metal type, the thickness of conductive walls and the deformation from perfect sphere. We implement a realistic SGW in COMSOL multiphysics and analyze its super-resolution properties. The realistic model is designed in accordance with the manufacturing requirements and technological limitations.

Super resolution using a modified Spherical Geodesic Waveguide suitable for manufacturing

The previous publications (Miñano et al, 2011) have shown that using a Spherical Geodesic Waveguide (SGW), it can be achieved the super-resolution up to ? /500 close to a set of discrete frequencies. These frequencies are directly connected with the well-known Schumann resonance frequencies of spherical symmetric systems. However, the Spherical Geodesic Waveguide (SGW) has been presented as an ideal system, in which the technological obstacles or manufacturing feasibility and their influence on final results were not taken into account. In order to prove the concept of superresolution experimentally, the Spherical Geodesic Waveguide is modified according to the manufacturing requirements and technological limitations. Each manufacturing process imposes some imperfections which can affect the experimental results. Here, we analyze the influence of the manufacturing limitations on the super-resolution properties of the SGW. Beside the theoretical work, herein, there has been presented the experimental results, as well.

Super-resolution properties of the Spherical Geodesic Waveguides using the perfect drain

Perfect drain for the Maxwell Fish Eye (MFE) is a nonmagnetic dissipative region placed in the focal point to absorb all the incident radiation without reflection or scattering. The perfect drain was recently designed as a material with complex permittivity ? that depends on frequency. However, this material is only a theoretical material, so it can not be used in practical devices. Recently, the perfect drain has been claimed as necessary to achieve super-resolution [Leonhard 2009, New J. Phys. 11 093040], which has increased the interest for practical perfect drains suitable for manufacturing. Here, we analyze the superresolution properties of a device equivalent to the MFE, known as Spherical Geodesic Waveguide (SGW), loaded with the perfect drain. In the SGW the source and drain are implemented with coaxial probes. The perfect drain is realized using a circuit (made of a resistance and a capacitor) connected to the drain coaxial probes. Superresolution analysis for this device is done in Comsol Multiphysics. The results of simulations predict the superresolution up to ? /3000 and optimum power transmission from the source to the drain.

Extreme super-resolution using the spherical geodesic waveguide

Leonhardt demonstrated (2009) that the 2D Maxwell Fish Eye lens (MFE) can focus perfectly 2D Helmholtz waves of arbitrary frequency, i.e., it can transport perfectly an outward (monopole) 2D Helmholtz wave field, generated by a point source, towards a "perfect point drain" located at the corresponding image point. Moreover, a prototype with λ/5 superresolution (SR) property for one microwave frequency has been manufactured and tested (Ma et al, 2010). Although this prototype has been loaded with an impedance different from the "perfect point drain", it has shown super-resolution property. However, neither software simulations nor experimental measurements for a broad band of frequencies have yet been reported. Here we present steady state simulations for two cases, using perfect drain as suggested by Leonhardt and without perfect drain as in the prototype. All the simulations have been done using a device equivalent to the MFE, called the Spherical Geodesic Waveguide (SGW). The results show the super-resolution up to λ/3000, for the system loaded with the perfect drain, and up to λ/500 for a not perfect load. In both cases super-resolution only happens for discrete number of frequencies. Out of these frequencies, the SGW does not show super-resolution in the analysis carried out.

Experimental evidence for super-resolution in the spherical geodesic waveguide

The previous publications (Miñano et al, 2011 and Gonzalez et al, 2012) have shown that using a Spherical Geodesic Waveguide (SGW) it can be achieved the super-resolution up to λ/3000, which is far below the classic Abbe diffraction limit, close to a set of discrete microwave frequencies. The SGW was designed and simulated in COMSOL as a thin geodesic waveguide bounded by an ideal and lossless metal. Herein we present the experimental results for a manufactured SGW, slightly modified due to fabrication requirements, showing the super-resolution up to λ/105.

Robust thermal face recognition using region classifiers

This paper presents a robust approach for recognition of thermal face images based on decision level fusion of 34 different region classifiers. The region classifiers concentrate on local variations. They use singular value decomposition (SVD) for feature extraction. Fusion of decisions of the region classifier is done by using majority voting technique. The algorithm is tolerant against false exclusion of thermal information produced by the presence of inconsistent distribution of temperature statistics which generally make the identification process difficult. The algorithm is extensively evaluated on UGC-JU thermal face database, and Terravic facial infrared database and the recognition performance are found to be 95.83% and 100%, respectively. A comparative study has also been made with the existing works in the literature.

Experimental evidence of super-resolution better than lambda/105 with positive refraction

Super-resolution (SR) systems surpassing the Abbe diffraction limit have been theoretically and experimentally demonstrated using a number of different approaches and technologies: using materials with a negative refractive index, utilizing optical super-oscillation, using a resonant metalens, etc. However, recently it has been proved theoretically that in the Maxwell fish-eye lens (MFE), a device made of positive refractive index materials, the same phenomenon takes place. Moreover, using a simpler device equivalent to the MFE called the spherical geodesic waveguide (SGW), an SR of up to λ/3000 was simulated in COMSOL. Until now, only one piece of experimental evidence of SR with positive refraction has been reported (up to λ/5) for an MFE prototype working at microwave frequencies. Here, experimental results are presented for an SGW prototype showing an SR of up to λ/105. The SGW prototype consists of two concentric metallic spheres with an air space in between and two coaxial ports acting as an emitter and a receiver. The prototype has been analyzed in the range 1 GHz to 1.3 GHz.

Higher-order regularization and morphological techniques for image segmentation

La segmentación de imágenes es un campo importante de la visión computacional y una de las áreas de investigación más activas, con aplicaciones en comprensión de imágenes, detección de objetos, reconocimiento facial, vigilancia de vídeo o procesamiento de imagen médica. La segmentación de imágenes es un problema difícil en general, pero especialmente en entornos científicos y biomédicos, donde las técnicas de adquisición imagen proporcionan imágenes ruidosas. Además, en muchos de estos casos se necesita una precisión casi perfecta. En esta tesis, revisamos y comparamos primero algunas de las técnicas ampliamente usadas para la segmentación de imágenes médicas. Estas técnicas usan clasificadores a nivel de pixel e introducen regularización sobre pares de píxeles que es normalmente insuficiente. Estudiamos las dificultades que presentan para capturar la información de alto nivel sobre los objetos a segmentar. Esta deficiencia da lugar a detecciones erróneas, bordes irregulares, configuraciones con topología errónea y formas inválidas. Para solucionar estos problemas, proponemos un nuevo método de regularización de alto nivel que aprende información topológica y de forma a partir de los datos de entrenamiento de una forma no paramétrica usando potenciales de orden superior. Los potenciales de orden superior se están popularizando en visión por computador, pero la representación exacta de un potencial de orden superior definido sobre muchas variables es computacionalmente inviable. Usamos una representación compacta de los potenciales basada en un conjunto finito de patrones aprendidos de los datos de entrenamiento que, a su vez, depende de las observaciones. Gracias a esta representación, los potenciales de orden superior pueden ser convertidos a potenciales de orden 2 con algunas variables auxiliares añadidas. Experimentos con imágenes reales y sintéticas confirman que nuestro modelo soluciona los errores de aproximaciones más débiles. Incluso con una regularización de alto nivel, una precisión exacta es inalcanzable, y se requeire de edición manual de los resultados de la segmentación automática. La edición manual es tediosa y pesada, y cualquier herramienta de ayuda es muy apreciada. Estas herramientas necesitan ser precisas, pero también lo suficientemente rápidas para ser usadas de forma interactiva. Los contornos activos son una buena solución: son buenos para detecciones precisas de fronteras y, en lugar de buscar una solución global, proporcionan un ajuste fino a resultados que ya existían previamente. Sin embargo, requieren una representación implícita que les permita trabajar con cambios topológicos del contorno, y esto da lugar a ecuaciones en derivadas parciales (EDP) que son costosas de resolver computacionalmente y pueden presentar problemas de estabilidad numérica. Presentamos una aproximación morfológica a la evolución de contornos basada en un nuevo operador morfológico de curvatura que es válido para superficies de cualquier dimensión. Aproximamos la solución numérica de la EDP de la evolución de contorno mediante la aplicación sucesiva de un conjunto de operadores morfológicos aplicados sobre una función de conjuntos de nivel. Estos operadores son muy rápidos, no sufren de problemas de estabilidad numérica y no degradan la función de los conjuntos de nivel, de modo que no hay necesidad de reinicializarlo. Además, su implementación es mucho más sencilla que la de las EDP, ya que no requieren usar sofisticados algoritmos numéricos. Desde un punto de vista teórico, profundizamos en las conexiones entre operadores morfológicos y diferenciales, e introducimos nuevos resultados en este área. Validamos nuestra aproximación proporcionando una implementación morfológica de los contornos geodésicos activos, los contornos activos sin bordes, y los turbopíxeles. En los experimentos realizados, las implementaciones morfológicas convergen a soluciones equivalentes a aquéllas logradas mediante soluciones numéricas tradicionales, pero con ganancias significativas en simplicidad, velocidad y estabilidad. ABSTRACT Image segmentation is an important field in computer vision and one of its most active research areas, with applications in image understanding, object detection, face recognition, video surveillance or medical image processing. Image segmentation is a challenging problem in general, but especially in the biological and medical image fields, where the imaging techniques usually produce cluttered and noisy images and near-perfect accuracy is required in many cases. In this thesis we first review and compare some standard techniques widely used for medical image segmentation. These techniques use pixel-wise classifiers and introduce weak pairwise regularization which is insufficient in many cases. We study their difficulties to capture high-level structural information about the objects to segment. This deficiency leads to many erroneous detections, ragged boundaries, incorrect topological configurations and wrong shapes. To deal with these problems, we propose a new regularization method that learns shape and topological information from training data in a nonparametric way using high-order potentials. High-order potentials are becoming increasingly popular in computer vision. However, the exact representation of a general higher order potential defined over many variables is computationally infeasible. We use a compact representation of the potentials based on a finite set of patterns learned fromtraining data that, in turn, depends on the observations. Thanks to this representation, high-order potentials can be converted into pairwise potentials with some added auxiliary variables and minimized with tree-reweighted message passing (TRW) and belief propagation (BP) techniques. Both synthetic and real experiments confirm that our model fixes the errors of weaker approaches. Even with high-level regularization, perfect accuracy is still unattainable, and human editing of the segmentation results is necessary. The manual edition is tedious and cumbersome, and tools that assist the user are greatly appreciated. These tools need to be precise, but also fast enough to be used in real-time. Active contours are a good solution: they are good for precise boundary detection and, instead of finding a global solution, they provide a fine tuning to previously existing results. However, they require an implicit representation to deal with topological changes of the contour, and this leads to PDEs that are computationally costly to solve and may present numerical stability issues. We present a morphological approach to contour evolution based on a new curvature morphological operator valid for surfaces of any dimension. We approximate the numerical solution of the contour evolution PDE by the successive application of a set of morphological operators defined on a binary level-set. These operators are very fast, do not suffer numerical stability issues, and do not degrade the level set function, so there is no need to reinitialize it. Moreover, their implementation is much easier than their PDE counterpart, since they do not require the use of sophisticated numerical algorithms. From a theoretical point of view, we delve into the connections between differential andmorphological operators, and introduce novel results in this area. We validate the approach providing amorphological implementation of the geodesic active contours, the active contours without borders, and turbopixels. In the experiments conducted, the morphological implementations converge to solutions equivalent to those achieved by traditional numerical solutions, but with significant gains in simplicity, speed, and stability.

Perfect imaging of point sources with positive refraction

The capability of a device called the Spherical Geodesic Waveguide (SGW) to produce images with details below the classic Abbe diffraction limit (super-resolution) is analyzed here. The SGW is an optical system equivalent (by means of Transformation Optics) to the Maxwell Fish Eye (MFE) refractive index distribution. Recently, it has been claimed that the necessary condition to get super-resolution in the MFE and the SGW is the use of a Perfect Point Drain (PPD). The PPD is a punctual receptor placed in the focal point that absorbs the incident wave, without reflection or scattering. A microwave circuit comprising three elements, the SGW, the source and the drain (two coaxial lines loaded with specific impedances) is designed and simulated in COMSOL. The super-resolution properties have been analyzed for different position of the source and drain and for two different load impedances: the PPD and the characteristic line impedance. The results show that in both cases super-resolution occurs only for discrete number of frequencies. Out of these frequencies, the SGW does not show SR in the analysis carried out.

Desarrollo de un sistema de reconocimiento facial

El objetivo principal alrededor del cual se desenvuelve este proyecto es el desarrollo de un sistema de reconocimiento facial. Entre sus objetivos específicos se encuentran: realizar una primera aproximación sobre las técnicas de reconocimiento facial existentes en la actualidad, elegir una aplicación donde pueda ser útil el reconocimiento facial, diseñar y desarrollar un programa en MATLAB que lleve a cabo la función de reconocimiento facial, y evaluar el funcionamiento del sistema desarrollado. Este documento se encuentra dividido en cuatro partes: INTRODUCCIÓN, MARCO TEÓRICO, IMPLEMENTACIÓN, y RESULTADOS, CONCLUSIONES Y LÍNEAS FUTURAS. En la primera parte, se hace una introducción relativa a la actualidad del reconocimiento facial y se comenta brevemente sobre las técnicas existentes para desarrollar un sistema biométrico de este tipo. En ella se justifican también aquellas técnicas que acabaron formando parte de la implementación. En la segunda parte, el marco teórico, se explica la estructura general que tiene un sistema de reconocimiento biométrico, así como sus modos de funcionamiento, y las tasas de error utilizadas para evaluar y comparar su rendimiento. Así mismo, se lleva a cabo una descripción más profunda sobre los conceptos y métodos utilizados para efectuar la detección y reconocimiento facial en la tercera parte del proyecto. La tercera parte abarca una descripción detallada de la solución propuesta. En ella se explica el diseño, características y aplicación de la implementación; que trata de un programa elaborado en MATLAB con interfaz gráfica, y que utiliza cuatro sistemas de reconocimiento facial, basados cada uno en diferentes técnicas: Análisis por componentes principales, análisis lineal discriminante, wavelets de Gabor, y emparejamiento de grafos elásticos. El programa ofrece además la capacidad de crear y editar una propia base de datos con etiquetas, dándole aplicación directa sobre el tema que se trata. Se proponen además una serie de características con el objetivo de ampliar y mejorar las funcionalidades del programa diseñado. Dentro de dichas características destaca la propuesta de un modo de verificación híbrido aplicable a cualquier rama de la biometría y un programa de evaluación capaz de medir, graficar, y comparar las configuraciones de cada uno de los sistemas de reconocimiento implementados. Otra característica destacable es la herramienta programada para la creación de grafos personalizados y generación de modelos, aplicable a reconocimiento de objetos en general. En la cuarta y última parte, se presentan al principio los resultados obtenidos. En ellos se contemplan y analizan las comparaciones entre las distintas configuraciones de los sistemas de reconocimiento implementados para diferentes bases de datos (una de ellas formada con imágenes con condiciones de adquisición no controladas). También se miden las tasas de error del modo de verificación híbrido propuesto. Finalmente, se extraen conclusiones, y se proponen líneas futuras de investigación. ABSTRACT The main goal of this project is to develop a facial recognition system. To meet this end, it was necessary to accomplish a series of specific objectives, which were: researching on the existing face recognition technics nowadays, choosing an application where face recognition might be useful, design and develop a face recognition system using MATLAB, and measure the performance of the implemented system. This document is divided into four parts: INTRODUCTION, THEORTICAL FRAMEWORK, IMPLEMENTATION, and RESULTS, CONCLUSSIONS AND FUTURE RESEARCH STUDIES. In the first part, an introduction is made in relation to facial recognition nowadays, and the techniques used to develop a biometric system of this kind. Furthermore, the techniques chosen to be part of the implementation are justified. In the second part, the general structure and the two basic modes of a biometric system are explained. The error rates used to evaluate and compare the performance of a biometric system are explained as well. Moreover, a description of the concepts and methods used to detect and recognize faces in the third part is made. The design, characteristics, and applications of the systems put into practice are explained in the third part. The implementation consists in developing a program with graphical user interface made in MATLAB. This program uses four face recognition systems, each of them based on a different technique: Principal Component Analysis (PCA), Fisher’s Linear Discriminant (FLD), Gabor wavelets, and Elastic Graph Matching (EGM). In addition, with this implementation it is possible to create and edit one´s tagged database, giving it a direct application. Also, a group of characteristics are proposed to enhance the functionalities of the program designed. Among these characteristics, three of them should be emphasized in this summary: A proposal of an hybrid verification mode of a biometric system; and an evaluation program capable of measuring, plotting curves, and comparing different configurations of each implemented recognition system; and a tool programmed to create personalized graphs and models (tagged graph associated to an image of a person), which can be used generally in object recognition. In the fourth and last part of the project, the results of the comparisons between different configurations of the systems implemented are shown for three databases (One of them created with pictures taken under non-controlled environments). The error rates of the proposed hybrid verification mode are measured as well. Finally, conclusions are extracted and future research studies are proposed.

Reconocimiento facial

El presente proyecto trata sobre uno de los campos más problemáticos de la inteligencia artificial, el reconocimiento facial. Algo tan sencillo para las personas como es reconocer una cara conocida se traduce en complejos algoritmos y miles de datos procesados en cuestión de segundos. El proyecto comienza con un estudio del estado del arte de las diversas técnicas de reconocimiento facial, desde las más utilizadas y probadas como el PCA y el LDA, hasta técnicas experimentales que utilizan imágenes térmicas en lugar de las clásicas con luz visible. A continuación, se ha implementado una aplicación en lenguaje C++ que sea capaz de reconocer a personas almacenadas en su base de datos leyendo directamente imágenes desde una webcam. Para realizar la aplicación, se ha utilizado una de las librerías más extendidas en cuanto a procesado de imágenes y visión artificial, OpenCV. Como IDE se ha escogido Visual Studio 2010, que cuenta con una versión gratuita para estudiantes. La técnica escogida para implementar la aplicación es la del PCA ya que es una técnica básica en el reconocimiento facial, y además sirve de base para soluciones mucho más complejas. Se han estudiado los fundamentos matemáticos de la técnica para entender cómo procesa la información y en qué se datos se basa para realizar el reconocimiento. Por último, se ha implementado un algoritmo de testeo para poder conocer la fiabilidad de la aplicación con varias bases de datos de imágenes faciales. De esta forma, se puede comprobar los puntos fuertes y débiles del PCA. ABSTRACT. This project deals with one of the most problematic areas of artificial intelligence, facial recognition. Something so simple for human as to recognize a familiar face becomes into complex algorithms and thousands of data processed in seconds. The project begins with a study of the state of the art of various face recognition techniques, from the most used and tested as PCA and LDA, to experimental techniques that use thermal images instead of the classic visible light images. Next, an application has been implemented in C + + language that is able to recognize people stored in a database reading images directly from a webcam. To make the application, it has used one of the most outstretched libraries in terms of image processing and computer vision, OpenCV. Visual Studio 2010 has been chosen as the IDE, which has a free student version. The technique chosen to implement the software is the PCA because it is a basic technique in face recognition, and also provides a basis for more complex solutions. The mathematical foundations of the technique have been studied to understand how it processes the information and which data are used to do the recognition. Finally, an algorithm for testing has been implemented to know the reliability of the application with multiple databases of facial images. In this way, the strengths and weaknesses of the PCA can be checked.