890 resultados para caranio-facial


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Placement of a single-tooth implant should be performed when a patient's facial growth has ceased. In this retrospective observational study, we evaluated if there was a difference in the timing of cessation of craniofacial growth in short, average, and long facial types. Based on the value of the angle between cranial base and mandibular plane (SN/MP angle), three groups comprising 48 subjects with short facial type (SF; SN/MP ≤28°), 77 with average facial type (AF; SN/MP ≥31.5° and ≤34.5°), and 44 with long facial type (LF; SN/MP ≥38°) were selected. Facial growth was assessed on lateral cephalograms taken at 15.4 years of age, and 2, 5, and 10 years later. Variables were considered to be stable when the difference between two successive measurements was less than 1 mm or 1°. We found no difference between facial types in the timing of cessation of facial growth. Depending on the variable, the mean age when variables became stable ranged from 18.0 years (Is-Pal in LF group) to 22.0 years (SN/MP in LF group). However, facial growth continued at the last follow-up in approximately 20% subjects. This study demonstrates that facial type is not associated with the timing of cessation of facial growth.

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OBJECTIVES To determine the relationship between nasolabial symmetry and esthetics in subjects with orofacial clefts. MATERIAL AND METHODS Eighty-four subjects (mean age 10 years, standard deviation 1.5) with various types of nonsyndromic clefts were included: 11 had unilateral cleft lip (UCL); 30 had unilateral cleft lip and alveolus (UCLA); and 43 had unilateral cleft lip, alveolus, and palate (UCLAP). A 3D stereophotogrammetric image of the face was taken for each subject. Symmetry and esthetics were evaluated on cropped 3D facial images. The degree of asymmetry of the nasolabial area was calculated based on all 3D data points using a surface registration algorithm. Esthetic ratings of various elements of nasal morphology were performed by eight lay raters on a 100 mm visual analog scale. Statistical analysis included ANOVA tests and regression models. RESULTS Nasolabial asymmetry increased with growing severity of the cleft (p = 0.029). Overall, nasolabial appearance was affected by nasolabial asymmetry; subjects with more nasolabial asymmetry were judged as having a less esthetically pleasing nasolabial area (p < 0.001). However, the relationship between nasolabial symmetry and esthetics was relatively weak in subjects with UCLAP, in whom only vermilion border esthetics was associated with asymmetry. CONCLUSIONS Nasolabial symmetry assessed with 3D facial imaging can be used as an objective measure of treatment outcome in subjects with less severe cleft deformity. In subjects with more severe cleft types, other factors may play a decisive role. CLINICAL SIGNIFICANCE Assessment of nasolabial symmetry is a useful measure of treatment success in less severe cleft types.

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OBJECTIVES Assess facial asymmetry in subjects with unilateral cleft lip (UCL), unilateral cleft lip and alveolus (UCLA), and unilateral cleft lip, alveolus, and palate (UCLP), and to evaluate which area of the face is most asymmetrical. METHODS Standardized three-dimensional facial images of 58 patients (9 UCL, 21 UCLA, and 28 UCLP; age range: 8.6-12.3 years) and 121 controls (age range 9-12 years) were mirrored and distance maps were created. Absolute mean asymmetry values were calculated for the whole face, cheek, nose, lips, and chin. One-way analysis of variance, Kruskal-Wallis, and t-test were used to assess the differences between clefts and controls for the whole face and separate areas. RESULTS Clefts and controls differ significantly for the whole face as well as in all areas. Asymmetry is distributed differently over the face for all groups. In UCLA, the nose was significantly more asymmetric compared with chin and cheek (P = 0.038 and 0.024, respectively). For UCL, significant differences in asymmetry between nose and chin and chin and cheek were present (P = 0.038 and 0.046, respectively). In the control group, the chin was the most asymmetric area compared to lip and nose (P = 0.002 and P = 0.001, respectively) followed by the nose (P = 0.004). In UCLP, the nose, followed by the lips, was the most asymmetric area compared to chin, cheek (P < 0.001 and P = 0.016, respectively). LIMITATIONS Despite division into regional areas, the method may still exclude or underrate smaller local areas in the face, which are better visualized in a facial colour coded distance map than quantified by distance numbers. The UCL subsample is small. CONCLUSION Each type of cleft has its own distinct asymmetry pattern. Children with unilateral clefts show more facial asymmetry than children without clefts.

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Oral-facial-digital type VI syndrome (OFDVI) is a rare phenotype of Joubert syndrome (JS). Recently, C5orf42 was suggested as the major OFDVI gene, being mutated in 9 of 11 families (82 %). We sequenced C5orf42 in 313 JS probands and identified mutations in 28 (8.9 %), most with a phenotype of pure JS. Only 2 out of 17 OFDVI patients (11.7 %) were mutated. A comparison of mutated vs. non-mutated OFDVI patients showed that preaxial and mesoaxial polydactyly, hypothalamic hamartoma and other congenital defects may predict C5orf42 mutations, while tongue hamartomas are more common in negative patients.

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Submitted in partial fulfillment of the requirements for a Certificate in Orthodontics, Dept. of Orthodontics, University of Connecticut Health Center, 1992

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Submitted in partial fulfillment of the requirements for a Certificate in Orthodontics, Dept. of Orthodontics, University of Connecticut Health Center, 1978

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El caso presentado nos plantea una situación de desorden fun- cional (limitación de la función articular), en apertura y laterali- dad, asociado a dolor intenso orofacial. La hipoplasia condílea unilateral se manifiesta como asimetría esqueletal con desplazamiento notable del mentón hacia el lado derecho, y mordida abierta anterior. Previamente se exponen conceptos básicos de crecimiento con- dilar e hipoplasia condilar.

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In social species, such as primates, facial appearances transmit a variety of social signals. Although it is suggested that the intense red colour of the face of the bald uakari monkey might be an indicator of health, this hypothesis still has not been verified. This study describes the histological structure of the skin of the face in the bald uakari, compared with other non-red neotropical primates, to better understand the maintenance of its colour. The facial skin of the bald uakari monkey is characterized by a thinner epidermis, absence of melanin pigments and a high density of vascular capillaries that spread below the epidermis. These vascular capillaries are larger and more tortuous than in other neotropical primates. The skin of the face of the bald uakari monkey allows a direct external assessment of haematological status, suggesting that the colour of the face would be an honest indicator of health, but could also signal sexual or behavioural states.

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Actualmente, las redes sociales se han instaurado como un mecamismo muy potente de comunicaci¿on y contacto entre individuos. Sin embargo, las pol¿?ticas de privacidad que normalmente han acompa?nado a estas redes sociales no han sido capaces de evitar el mal uso de las mismas en temas relacionados con protecci¿on a menores. El caso m¿as significativo es el de adultos, haci¿endose pasar por menores. Este trabajo investiga la viabilidad del uso de t¿ecnicas biom¿etricas basadas en rasgos faciales para la detecci¿on de rangos de edad, con el prop¿osito de evitar que adultos se hagan pasar por menores, o incluso que ciertos menores puedan acceder a redes sociales, cuyo acceso debe estar trestringido por su edad. Los resultados muestran que es posible hacer esta distinci¿on entre adultos y menores, seleccionando edades umbrales cercanas a los 18 a? nos, con tasas de acierto cercanas al 80 %, y empleando clasificadores basados en m¿aquinas de vector soporte (SVMs) lineales.

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There is an increasing need of easy and affordable technologies to automatically generate virtual 3D models from their real counterparts. In particular, 3D human reconstruction has driven the creation of many clever techniques, most of them based on the visual hull (VH) concept. Such techniques do not require expensive hardware; however, they tend to yield 3D humanoids with realistic bodies but mediocre faces, since VH cannot handle concavities. On the other hand, structured light projectors allow to capture very accurate depth data, and thus to reconstruct realistic faces, but they are too expensive to use several of them. We have developed a technique to merge a VH-based 3D mesh of a reconstructed humanoid and the depth data of its face, captured by a single structured light projector. By combining the advantages of both systems in a simple setting, we are able to reconstruct realistic 3D human models with believable faces.

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We propose a new method to automatically refine a facial disparity map obtained with standard cameras and under conventional illumination conditions by using a smart combination of traditional computer vision and 3D graphics techniques. Our system inputs two stereo images acquired with standard (calibrated) cameras and uses dense disparity estimation strategies to obtain a coarse initial disparity map, and SIFT to detect and match several feature points in the subjects face. We then use these points as anchors to modify the disparity in the facial area by building a Delaunay triangulation of their convex hull and interpolating their disparity values inside each triangle. We thus obtain a refined disparity map providing a much more accurate representation of the the subjects facial features. This refined facial disparity map may be easily transformed, through the camera calibration parameters, into a depth map to be used, also automatically, to improve the facial mesh of a 3D avatar to match the subjects real human features.

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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.

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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.