Made available in DSpace on 2014-06-12T18:34:10Z (GMT). No. of bitstreams: 2 arquivo4048_1.pdf: 1733143 bytes, checksum: 0d01f804defcf07ba70a1b6a5fec7b49 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2009 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / O trabalho desenvolvido aqui consiste num estudo das relações entre pessoas que exercem funções diferentes em duas empresas ligadas à Economia de Comunhão (EdC), sediadas no estado de São Paulo. A EdC surgiu no âmbito de um movimento social cristão, o Movimento dos Focolares, e propõe um modelo de gestão econômica e de pessoas baseado no princípio da fraternidade. O estudo apresentado nesta dissertação analisa como se constituem as relações entre pessoas que exercem cargos de diferentes níveis hierárquicos, a partir dos estudos da Sociolinguística Interacional, com base nos conceitos de enquadre (Goffman, 1974; Tannen & Wallat, 1987/2002), alinhamento (Goffman, 1979/2002), face (Goffman, 1967/1980) e polidez (Brown e Levinson, 1987). É um estudo qualitativo interpretativo, realizado numa perspectiva etnográfica de observação participante. O corpus da pesquisa consiste em gravações de reuniões, entrevistas, anotações de campo e documentos escritos. A seleção dos dados analisados foi feita conforme os objetivos da pesquisa, para dar maior visibilidade às interações entre os participantes. O estudo demonstra que as duas empresas têm características peculiares que propiciam abertura na interação entre superior e subordinado, possibilitando aos funcionários que exercem cargos hierarquicamente inferiores influenciar em decisões que competem a funcionários de cargos superiores, embora indique também que essas empresas estão em estágios diferentes de desenvolvimento da proposta de gestão da EdC

Made available in DSpace on 2014-06-12T18:38:01Z (GMT). No. of bitstreams: 2 arquivo8435_1.pdf: 3670000 bytes, checksum: ef6758e2dfcc1f8d48e28719dd0f943b (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2005 / Este trabalho propõe uma análise da construção do sentido durante um programa de TV. Muitos estudos já se debruçaram sobre a problemática da interação.O ineditismo do nosso estudo se dá por analisarmos o sentido que se constitui em uma interação pré-produzida ou idealizada no sitcom, classificado como gênero discursivo televisivo. O corpus analisado foi a comédia de situação Os Normais, exibida pela Rede Globo de televisão, entre 2001-2003, que se tornou um modelo-padrão para outras produções do gênero. A perspectiva da Análise do Discurso, que nós utilizamos, enfoca o aspecto sócio-pragmático do discurso, particularmente, no tocante às estratégias argumentativas, utilizadas na preservação e manutenção do jogo de linguagem entre os interactantes. Nosso referencial teórico fundamenta-se na ótica sócio-interacionista e dialógica de Mikhail Bakhtin ([1979]2000) e ([1929]2000), na análise do discurso sóciopragmática de Dominique Maingueneau (2002/2005), e nas observações teóricas de Ingedore Koch ([1993] 2003) e ([1997]2002), relativas à perspectiva interacional da conversação face a face para a construção de sentido de textos orais e escritos. Objetivamos neste trabalho refletir sobre quais são os mecanismos lingüístico-discursivos, considerando suas condições de produção, em que o sitcom se baseou para constituir o efeito de sentido do humor privilegiado pelos telespectadores. Outros fatores, também, foram considerados em nossa análise como formato de programa televisivo diferenciado, interpretação e autonomia dos atores que contribuíram para uma interação híbrida nas fronteiras do escrito com o oral pelas quais flutua o gênero televisivo que investigamos

Orientador: Miguel Carlos Madeira / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Odontologia de Piracicaba / Made available in DSpace on 2018-07-15T00:59:09Z (GMT). No. of bitstreams: 1 Oliveira_JoseAmericode_M.pdf: 1680232 bytes, checksum: 91db64f1d000b5e54cebf5db1bc6231b (MD5) Previous issue date: 1977 / Resumo: Não informado / Abstract: Not informed. / Mestrado / Morfologia / Mestre em Biologia Buco-Dental

M. Comm. / Malicious acts such as fraud and terrorisms are continually becoming a more pressing threat. The need is growing daily for a cheap, non-intrusive technology, that does not make use of specialized equipment, which can identify individuals with or without their knowledge or permission, over the internet or in the public domain. The answer to this problem might be digital facial recognition, the authentication of a person according to the measurements and shape of his facial patterns (nodal points). Thus far the technology has primarily been used by law enforcement. The great strength of facial recognition is that it can scan multiple people in an area quickly, with or without their interaction with the system. The purpose of facial recognition surveillance is to implement it anywhere possible, for example shopping centres, street corners, hotel lobbies or train stations, and to be able to identify any individual finding himself in any of these areas. Also, if a larger system can be implemented, we would be able to track any individual wherever he goes. Through this, any suspicious character can be monitored and tracked if the need arises, ensuring that people can live in a much safer world.

Abstract Frostbite of the face and ears is a common problem in cold winters. Application of an emollient on the face is a traditional way to prevent frostbite in Finland. The preliminary results of an epidemiological study on frostbite in Finnish conscripts unexpectedly showed that the use of cold protecting emollients increased the risk of facial frostbite. This finding motivated studies on the effects and use of cold protecting emollients. 830 male Finnish conscripts answered a questionnaire concerning the use of cold protecting emollients, subjective experience of using them in cold and cumulative incidence of frostbite in the ears and face. Risk factors of frostbite were investigated in a prospective epidemiological study including 913 Finnish conscripts needing medical attention for frostbite of the ears or face and their 2478 matched, uninjured controls. Thermal properties of four different emollients were studied in vitro with a skin model and in vivo in experimental cold exposures of test persons. Test emollient was applied on one half of the face, as the other half acted as control. The skin temperatures of the face-halves were compared symmetrically by thermistors and infrared thermography. Subjective sensation of thermal half-difference was also registered. 21% of the conscripts had used emollients in the cold, a majority with an experience of protection. 47% of the conscripts had had frostbite in the head (42% in the ears and 23% on the face). There was a statistically significant correlation between the use of emollients and the incidence of facial frostbite in both epidemiological studies. Applying protective emollients formed an independent risk factor for frostbite of the cheeks, nose and ear lobes (odds ratios 3.3-5.6). The thermal insulation of test emollients on the skin model was minimal. On living skin, the applied half was somewhat cooler in a majority of comparisons. However, white petrolatum gave often a subjective perception of a warming effect. False sensation of safety may form the principal cause for the increased risk of frostbite associated with the use of emollients. When the warning symptoms of cold are weak, necessary protective measures are not carried out.

Abstract Image appearance descriptors are needed for different computer vision applications dealing with, for example, detection, recognition and classification of objects, textures, humans, etc. Typically, such descriptors should be discriminative to allow for making the distinction between different classes, yet still robust to intra-class variations due to imaging conditions, natural changes in appearance, noise, and other factors. The purpose of this thesis is the development and analysis of photometric descriptors for the appearance of real life images. The two application areas included in this thesis are face recognition and texture classification. To facilitate the development and analysis of descriptors, a general framework for image description using statistics of quantized filter bank responses modeling their joint distribution is introduced. Several texture and other image appearance descriptors, including the local binary pattern operator, can be presented using this model. This framework, within which the thesis is presented, enables experimental evaluation of the significance of each of the components of this three-part chain forming a descriptor from an input image. The main contribution of this thesis is a face representation method using distributions of local binary patterns computed in local rectangular regions. An important factor of this contribution is to view feature extraction from a face image as a texture description problem. This representation is further developed into a more precise model by estimating local distributions based on kernel density estimation. Furthermore, a face recognition method tolerant to image blur using local phase quantization is presented. The thesis presents three new approaches and extensions to texture analysis using quantized filter bank responses. The first two aim at increasing the robustness of the quantization process. The soft local binary pattern operator accomplishes this by making a soft quantization to several labels, whereas Bayesian local binary patterns make use of a prior distribution of labelings, and aim for the one maximizing the a posteriori probability. Third, a novel method for computing rotation invariant statistics from histograms of local binary pattern labels using the discrete Fourier transform is introduced. All the presented methods have been experimentally validated using publicly available image datasets and the results of experiments are presented in the thesis. The face description approach proposed in this thesis has been validated in several external studies, and it has been utilized and further developed by several research groups working on face analysis.

In the field of computer vision, face detection concerns the positive identification of the faces of people within still images or video streams, which is extremely useful for applications such as counting, tracking, and recognition. When applied in large-scale environments, such as lecture theatres, we have found that existing technology can struggle greatly in detecting faces due primarily to the indiscernibility of their features, caused by partial occlusion, problematic orientation, and a lack of focus or resolution. We attempt to overcome this issue by proposing an adaptive framework, capable of collating the results of numerous existing detection systems in order to significantly improve recall rates. This approach uses supplementary modalities, invariant to the issues posed to features, to eliminate false detections from collated sets and allow us to produce results with extremely high confidence. The properties we have selected as the bases of detection classification are size and colour, as we believe that filters that consider them can be constructed adaptively, on a per-image basis, ensuring that the variabilities inherent to large-scale imagery can be fully accounted for, and that false detections and actual faces can be accurately distinguished between on a consistent basis. The application of principal component analysis to precise face detection results yields planar size distribution models that we can use to discard results that are either too large or too small to realistically represent faces within given images. Classifying a detection according to the correspondence of its general colour tone to the expected colour of skin is a more complex matter, however, as the apparent colour of skin is highly dependent upon incident illumination, and existing techniques are neither specific nor flexible enough to model it as accurately as we believe possible. Therefore, we propose another system, which will be able to adaptively model skin colour distributions according to the Gaussian probability densities exhibited by the colours of precise face detections. Furthermore, it will be suitable for independent application to real-time skin segmentation tasks as a result of considerable optimisation. This thesis details the design, the development, and the implementation of our systems, and thoroughly evaluates them with regards to the accuracy of their results and the efficiency of their performances, thereby establishing fully the suitability of them for solving certain types of presented problems.

No description available.

This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

With more and more images being uploaded to social networks each day, the resources for identifying a large portion of the world are available. However the tools to harness and utilize this information are not sufficient. This thesis presents a system, called PhacePhinder, which can build a face database from a social network and have it accessible from mobile devices. Through combining existing technologies, this is made possible. It also makes use of a fusion probabilistic latent semantic analysis to determine strong connections between users and content. Using this information we can determine the most meaningful social connection to a recognized person, allowing us to inform the user of how they know the person being recognized. We conduct a series of offline and user tests to verify our results and compare them to existing algorithms. We show, that through combining a user’s friendship information as well as picture occurrence information, we can make stronger recommendations than based on friendship alone. We demonstrate a working prototype that can identify a face from a picture taken from a mobile phone, using a database derived from images gathered directly from a social network, and return a meaningful social connection to the recognized face.