Orientador: Osmir Batista de Oliveira Júnior / Banca: Renata Corrêa Pascotto / Banca: Marcelo Ferrarezi de Andrade / Resumo: O presente estudo se propôs a avaliar o grau de percepção da atratividade do sorriso em função dos seguintes fatores: variações das normas de beleza, conhecimento dos avaliadores e enquadramento fotográfico. Alterações digitais foram realizadas nos sorrisos de fotografias faciais de dois indivíduos de sexos distintos, a fim de enquadrá-las nas normas estéticas estabelecidas pela literatura. Após as alterações, as fotografias foram cortadas em âmbito bucal para que os sorrisos também fossem avaliados neste enquadramento. Para cada enquadramento foram criados 11 sorrisos: uma do sorriso ideal controle (I) (sorriso ideal segundo normas consideradas) e 10 variações individuais de cada uma das normas consideradas a saber: 1) Desvio de linha média- 2mm (LM2) e 3 mm (LM3); 2) Linha do sorriso- linha do sorriso reta (LSR) e linha do sorriso reversa (LSRV); 3) Angulação incisivos laterais- 10º para mesial (A10m) e 10º para distal (A10d); 4) Diastema: 0.5mm e 1mm e 5) Proporção dental- proporção de Alber e proporção de Platão, totalizando 44 fotografias. Estas foram avaliadas individualmente por 4 examinadores, 2 especialistas em dentística e 2 leigos, utilizando a escala visual analógica (VAS), em duas sessões de análise. Puderam ser observadas diferenças entre avaliações feitas por dentistas e leigos. Para algumas fotografias a atratividade do sorriso se modificou quando avaliado este nos diferentes enquadramentos. Foi observado que o sorriso ideal controle, de ambos sexos e âmbitos de avaliações, mostrou maior atratividade que os sorrisos com variações nas normas estéticas. Os sorrisos que continham grandes diastemas e linha do sorriso reta ou invertida obtiveram maior prejuízo da atratividade do sorriso. As três proporções matemáticas (Alber, Platão e Proporção Áurea) determinaram elevados níveis de atratividade... (Resumo completo, clicar acesso eletrônico abaixo). / Abstract: The objective of the present study was to evaluate the perception degree of the smile attractiveness due to the following factors: variations of beauty patterns, knowledge of the examiners and photographic framing. Digital alterations were made in facial photographs of 2 individuals of both sexes in order to fit them into the esthetical patterns established by the literature. After the alterations, the photographs focused the mouth so as the smiles could also be evaluated in this framing. For each framing, eleven smiles were created: one of the control ideal smile (I) (ideal smile according to the patterns considered) and 10 individual variations of each one of the patterns considered, as follows: 1) midline deviation - 2mm (LM2) and 3 mm (LM3); 2) Smile line - straight smile line (LSR) and inverted smile line (LSRV); 3) Lateral incisors angulation - 10º towards mesial (A10m) and 10º towards distal (A10d); 4) Diastema: 0.5mm and 1mm and 5) Dental proportion - Alber's proportion and Plato's proportion, totaling 44 photographs, which were individually evaluated by 4 examiners, 2 specialists in operative dentistry and 2 laypeople, using the analogical visual scale (VAS), in 2 sessions of analysis. Differences could be observed between the evaluations made by dentists and laypeople. The smile attractiveness has changed for some photographs when they were evaluated in the different framing alterations. It was possible to observe that the control ideal smile of both sexes and different evaluation ambits showed a more intense attractiveness than the smiles with variations of the esthetical patterns. Large diastemas and also straight or inverted smile lines were the conditions which strongly harmed the smile attractiveness. The three mathematical proportions (Alber's, Plato's and The Golden Proportion) determined high levels of... (Complete abstract, click electronic address below). / Mestre

Orientador: Luiz Gonzaga Gandini Júnior / Banca: Lídia Parsekian Martins / Banca: Alexandre Fortes Drummond / Resumo: O corredor bucal é definido como o espaço que existe bilateralmente entre a superfície vestibular dos dentes superiores posteriores visíveis e a comissura labial durante o sorriso. Este espaço escuro também é conhecido como espaço negativo. O objetivo da presente pesquisa foi analisar o corredor bucal durante o sorriso de 150 indivíduos de 10 a 19 anos de idade, verificando se há mudança no tamanho desse espaço em diferentes idades, se há diferença entre os gêneros e se existe uma relação de proporção entre a distância inter pré-molares, a largura inter comissura e o corredor bucal. Foram realizadas fotografias digitais padronizadas em norma frontal do sorriso amplo posado que foram transferidas para um computador e os contornos das imagens dos corredores bucais e sua medida linear foram delimitados e calculados pelo programa Image Tool 3.0. Uma linha entre as comissuras labiais direita e esquerda foi definida medindo a largura inter comissura. A área inter labial do sorriso e do corredor bucal foi delimitada e calculada. As distâncias entre as cúspides vestibulares dos primeiros pré-molares superiores foram medidas em modelos de gesso comum e as mesmas foram transferidas para um computador para posteriores comparações. A análise dos dados foi realizada obtendo estimativas por intervalo de confiança, análise de variância com dois critérios de classificação, comparação múltipla de médias e coeficiente de correlação de Pearson. O corredor bucal aumentou com a idade. Os indivíduos do gênero masculino apresentam corredor bucal maior que os do gênero feminino, porém em relação ao percentual da largura inter comissura não há diferença entre os gêneros. / Abstract: The buccal corridor is defined as the space that exists bilaterally between the vestibular surface of the subsequent superior teeth visible and the labial comissure during the smile. This dark space is also known as negative space. The objective of the present research is to analyze the buccal corridor during the smile of 150 individuals from 10 to 19 years of age, verifying if there is change in the size of that space in different ages and if exists a relationship of proportion among the inter premolar distance, the inter comissure width and the buccal corridor. Digital standardized pictures were accomplished in frontal norm of the posed wide smile that were transferred for a computer and the outlines of the images of the buccal corridors and linear measure were delimited and calculated by the program Image Tool 3.0. A line between the right and left comissures was defined measuring the inter comissure width. The inter labial area of the smile and buccal corridors were delimited and calculated. The distances among the vestibular cusps of the first superior premolars were measured in casts of common plaster and were transferred for a computer for subsequent comparisons. The analysis of the data was accomplished obtaining confidence intervals, analysis of variance with two classification criteria, multiple mean test and Pearson correlation coefficient to complete data. Buccal corridor increases with age. Males have bigger buccal corridor than females, but there is no difference between gender when calculated as percentage related with the inter comissure width. / Mestre

La técnica de cirugía refractiva láser a través de la extracción de un lentículo por una microincisión SMILE (Small Incision Lenticule Extraction), representa una técnica novedosa para la corrección de la miopía y un cambio de paradigma en torno a los procedimientos anteriores de cirugía refractiva láser. En esta Tesis doctoral por compendio de publicaciones se evalúan los resultados de eficacia, seguridad y predictibilidad para las primeras intervenciones de un cirujano experimentado en cirugía refractiva sin experiencia previa en SMILE. Estos resultados clínicos podrían estar condicionados por las características biomecánicas de la córnea intervenida. En esta Tesis doctoral se estudian las variables de confusión en pacientes operados de SMILE y se proponen soluciones para el diseño de estudios con el fin de minimizar el efecto de éstas y así poder detectar cuando los cambios en los parámetros de biomecánica se deben a una modificación de la rigidez corneal y no a un cambio en las variables de confusión. Finalmente, se analizan los parámetros más actuales de la tonometría dinámica de Scheimpflug y se propone una nueva variable conocida como densitometría dinámica por su posible aportación de información sobre la biomecánica e hidratación corneal.

La técnica de cirugía refractiva láser a través de la extracción de un lentículo por una microincisión SMILE (Small Incision Lenticule Extraction), representa una técnica novedosa para la corrección de la miopía y un cambio de paradigma en torno a los procedimientos anteriores de cirugía refractiva láser. En esta Tesis doctoral por compendio de publicaciones se evalúan los resultados de eficacia, seguridad y predictibilidad para las primeras intervenciones de un cirujano experimentado en cirugía refractiva sin experiencia previa en SMILE. Estos resultados clínicos podrían estar condicionados por las características biomecánicas de la córnea intervenida. En esta Tesis doctoral se estudian las variables de confusión en pacientes operados de SMILE y se proponen soluciones para el diseño de estudios con el fin de minimizar el efecto de éstas y así poder detectar cuando los cambios en los parámetros de biomecánica se deben a una modificación de la rigidez corneal y no a un cambio en las variables de confusión. Finalmente, se analizan los parámetros más actuales de la tonometría dinámica de Scheimpflug y se propone una nueva variable conocida como densitometría dinámica por su posible aportación de información sobre la biomecánica e hidratación corneal.

No / With its numerous applications, automatic facial emotion recognition has recently become a very active area of research. Yet there has been little detailed study of the dynamic components of facial expressions. This article reviews research that shows gender is encoded in the dynamics of a smile, and how it may be possible to use the dynamic components of facial expressions as a form of biometric.

No description available.

The annals of orthodontics are filled with studies aimed to understand how extraction orthodontic treatment might change the face. Although many studies have addressed profile changes due to extraction treatment, fewer studies have focused on how extractions change a patients smile. With the advent of surface imaging systems such as 3dMD, it is now possible to visualize the smile, and any changes incurred during orthodontic treatment, in three dimensions. Subjects for this study were chosen from the pool of 11-18 year old patients treated at the Podray Orthodontic Clinic at the Temple University Kornberg School of Dentistry. Subjects were Cl II patients, and must have been treated with either extraction of any combination of premolars or treated without extraction. Subjects were divided into four experimental groups based on two characteristics- mandibular angle (those with angles greater than 28o versus those with angles less than 28o) and treatment (extraction versus non-extraction). The resulting groups were separated as follows: high-angle extraction patients (n=8), low-angle extraction patients (n=6), high-angle non-extraction patients (n=7), and low-angle non-extraction patients (n=15). For each subject initial and final 3dMD images were superimposed using 3dMD Vultus software. A color histogram was constructed to visualize changes during treatment. The cheeks, commissures, upper and lower lips, chin, and nose, were also landmarked, and the changes in these landmarks were calculated. Volume changes were also calculated between pre and post treatment 3D data. Results showed that the lower lip and right commissure changes between high-angle extraction and non-extraction groups were statistically significant. A qualitative analysis of the histograms further supported these findings. In general, a greater change in soft tissue landmarks and soft tissue volumes could be seen in high-angle patients than low-angle patients. Differences in the changes that result from treatment type (extraction vs. non-extraction) were seen in the high-angle group. In contrast, similar changes result from treatment type (extraction vs. non-extraction) in the low-angle groups. Furthermore, the lip changes seen in extraction patients upon smiling are very similar to those changes seen in the same patient in repose. Most interestingly, soft tissue differences of the face due to treatment, growth, or both, seem to disappear upon smiling, with the exception of the lips. Qualitative assessment of these changes in the smile might be a more appropriate method for identifying soft tissue changes than statistical analyses. Similar studies with larger sample sizes are a promising direction for future research. / Oral Biology

No / Gender classification has multiple applications including, but not limited to, face perception, age, ethnicity and identity analysis, video surveillance and smart human computer interaction. The majority of computer based gender classification algorithms analyse the appearance of facial features predominantly based on the texture of the static image of the face. In this paper, we propose a novel algorithm for gender classification using the smile dynamics without resorting to the use of any facial texture information. Our experiments suggest that this method has great potential for finding indicators of gender dimorphism. Our approach was tested on two databases, namely the CK+ and the MUG, consisting of a total of 80 subjects. As a result, using the KNN algorithm along with 10-fold cross validation, we achieve an accurate classification rate of 80% for gender simply based on the dynamics of a person's smile.

Yes / Automatic gender classification has become a topic of great interest to the visual computing research community in recent times. This is due to the fact that computer-based automatic gender recognition has multiple applications including, but not limited to, face perception, age, ethnicity, identity analysis, video surveillance and smart human computer interaction. In this paper, we discuss a machine learning approach for efficient identification of gender purely from the dynamics of a person’s smile. Thus, we show that the complex dynamics of a smile on someone’s face bear much relation to the person’s gender. To do this, we first formulate a computational framework that captures the dynamic characteristics of a smile. Our dynamic framework measures changes in the face during a smile using a set of spatial features on the overall face, the area of the mouth, the geometric flow around prominent parts of the face and a set of intrinsic features based on the dynamic geometry of the face. This enables us to extract 210 distinct dynamic smile parameters which form as the contributing features for machine learning. For machine classification, we have utilised both the Support Vector Machine and the k-Nearest Neighbour algorithms. To verify the accuracy of our approach, we have tested our algorithms on two databases, namely the CK+ and the MUG, consisting of a total of 109 subjects. As a result, using the k-NN algorithm, along with tenfold cross validation, for example, we achieve an accurate gender classification rate of over 85%. Hence, through the methodology we present here, we establish proof of the existence of strong indicators of gender dimorphism, purely in the dynamics of a person’s smile.

No / This chapter is concerned with the discussion of a computational framework to aid with gender classification in an automated fashion using the dynamics of a smile. The computational smile dynamics framework we discuss here uses the spatio-temporal changes on the face during a smile. Specifically, it uses a set of spatial and temporal features on the overall face. These include the changes in the area of the mouth, the geometric flow around facial features and a set of intrinsic features over the face. These features are explicitly derived from the dynamics of the smile. Based on it, a number of distinct dynamic smile parameters can be extracted which can then be fed to a machine learning algorithm for gender classification.