Abstract The purpose of this research has been to show with applications that polyhedral scenes can be modeled in real time with a single video camera. Sometimes this can be done very efficiently without any special image processing hardware. The developed vision sensor estimates its three-dimensional position with respect to the environment and models it simultaneously. Estimates become recursively more accurate when objects are approached and observed from different viewpoints. The modeling process starts by extracting interesting tokens, like lines and corners, from the first image. Those features are then tracked in subsequent image frames. Also some previously taught patterns can be used in tracking. A few features in the same image are extracted. By this way the processing can be done at a video frame rate. New features appearing can also be added to the environment structure. Kalman filtering is used in estimation. The parameters in motion estimation are location and orientation and their first derivates. The environment is considered a rigid object in respect to the camera. The environment structure consists of 3-D coordinates of the tracked features. The initial model lacks depth information. The relational depth is obtained by utilizing facts such as closer points move faster on the image plane than more distant ones during translational motion. Additional information is needed to obtain absolute coordinates. Special attention has been paid to modeling uncertainties. Measurements with high uncertainty get less weight when updating the motion and environment model. The rigidity assumption is utilized by using shapes of a thin pencil for initial model structure uncertainties. By observing continuously motion uncertainties, the performance of the modeler can be monitored. In contrast to the usual solution, the estimations are done in separate state vectors, which allows motion and 3-D structure to be estimated asynchronously. In addition to having a more distributed solution, this technique provides an efficient failure detection mechanism. Several trackers can estimate motion simultaneously, and only those with the most confident estimates are allowed to update the common environment model. Tests showed that motion with six degrees of freedom can be estimated in an unknown environment. The 3-D structure of the environment is estimated simultaneously. The achieved accuracies were millimeters at a distance of 1-2 meters, when simple toy-scenes and more demanding industrial pallet scenes were used in tests. This is enough to manipulate objects when the modeler is used to offer visual feedback.

Veículos autônomos são importantes para a execução de missões dos mais variados tipos, reduzindo riscos aos seres humanos e executando as missões de uma maneira mais eficiente. Neste contexto existem os veículos aéreos não tripulados que são cada vez mais utilizados em missões de vigilância, reconhecimento, resgate, entre outras. Uma das características destes veículos é realizar as missões de maneira autônoma, sem a intervenção de operadores humanos. Desta forma, é necessário que existam formas de detectar aproximações perigosas com outras aeronaves e objetos que possam causar risco de colisão e, consequentemente a perda de ativos de alto valor ou até mesmo vidas humanas e, posteriormente realizar o desvio necessário. Neste cenário foi proposto o MOSAIC, um sistema de detecção e desvio de obstáculos utilizando visão monocular para veículos aéreos de pequeno porte. Para isto, foi desenvolvido um método de estimativa da posição tridimensional dos obstáculos a partir de imagens monoculares e propostas melhorias em algoritmos de detecção. A validação do sistema foi obtida por meio de experimentos simulados e reais sobre cada módulo e os resultados obtidos foram promissores, apresentando um erro de apenas 9,75% em ambientes sem restrições e distâncias de até 20 metros. Com isto, os resultados se mostram melhores que os demais algoritmos encontrados no estado da arte em que o erro é menor que 10% apenas em ambientes controlados e distâncias de até 5 metros. / Autonomous vehicles can be used for different kinds of missions reducing risks to human life and being more efficient. In this context, unmanned aerial vehicles play an important role on surveillance, recognition and rescue missions, among others. Due to the mission nature, these vehicles need to perform actions without human intervention, which requires that dangerous approximations to others aerial vehicles or objects to be detected and properly avoided. This leads to the creation of MOSAIC, an obstacle avoidance system based on monocular vision designed to meet the requirements of miniature air vehicles. A novel approach to estimate obstacle three-dimensional position based on monocular vision was developed and some improvements in the detection algorithm were proposed. The system validation was obtained through simulated and real experiments in which each module could be validated. Promising results were obtained showing an error under 9.75% in unconstrained environments and distance up to 20 meters. This results were better than the algorithms and approaches described in the state of the art where errors are under 10% only on constrained environments and distance up to 5 meters.

Veículos autônomos são importantes para a execução de missões dos mais variados tipos, reduzindo riscos aos seres humanos e executando as missões de uma maneira mais eficiente. Neste contexto existem os veículos aéreos não tripulados que são cada vez mais utilizados em missões de vigilância, reconhecimento, resgate, entre outras. Uma das características destes veículos é realizar as missões de maneira autônoma, sem a intervenção de operadores humanos. Desta forma, é necessário que existam formas de detectar aproximações perigosas com outras aeronaves e objetos que possam causar risco de colisão e, consequentemente a perda de ativos de alto valor ou até mesmo vidas humanas e, posteriormente realizar o desvio necessário. Neste cenário foi proposto o MOSAIC, um sistema de detecção e desvio de obstáculos utilizando visão monocular para veículos aéreos de pequeno porte. Para isto, foi desenvolvido um método de estimativa da posição tridimensional dos obstáculos a partir de imagens monoculares e propostas melhorias em algoritmos de detecção. A validação do sistema foi obtida por meio de experimentos simulados e reais sobre cada módulo e os resultados obtidos foram promissores, apresentando um erro de apenas 9,75% em ambientes sem restrições e distâncias de até 20 metros. Com isto, os resultados se mostram melhores que os demais algoritmos encontrados no estado da arte em que o erro é menor que 10% apenas em ambientes controlados e distâncias de até 5 metros. / Autonomous vehicles can be used for different kinds of missions reducing risks to human life and being more efficient. In this context, unmanned aerial vehicles play an important role on surveillance, recognition and rescue missions, among others. Due to the mission nature, these vehicles need to perform actions without human intervention, which requires that dangerous approximations to others aerial vehicles or objects to be detected and properly avoided. This leads to the creation of MOSAIC, an obstacle avoidance system based on monocular vision designed to meet the requirements of miniature air vehicles. A novel approach to estimate obstacle three-dimensional position based on monocular vision was developed and some improvements in the detection algorithm were proposed. The system validation was obtained through simulated and real experiments in which each module could be validated. Promising results were obtained showing an error under 9.75% in unconstrained environments and distance up to 20 meters. This results were better than the algorithms and approaches described in the state of the art where errors are under 10% only on constrained environments and distance up to 5 meters.

Este trabalho aborda o problema da estimação de profundidade a partir de imagens monoculares (SIDE), com foco em melhorar a qualidade das predições de redes neurais profundas. Em um cenário de aprendizado supervisionado, a qualidade das predições está intrinsecamente relacionada aos rótulos de treinamento, que orientam o processo de otimização. Para cenas internas, sensores de profundidade baseados em escaneamento por luz estruturada (Ex.: Kinect) são capazes de fornecer mapas de profundidade densos, embora de curto alcance. Enquanto que para cenas externas, consideram-se LiDARs como sensor de referência, que comparativamente fornece medições mais esparsas, especialmente em regiões mais distantes. Em vez de modificar a arquitetura de redes neurais para lidar com mapas de profundidade esparsa, este trabalho introduz um novo método de densificação para mapas de profundidade, usando o framework de Mapas de Hilbert. Um mapa de ocupação contínuo é produzido com base nos pontos 3D das varreduras do LiDAR, e a superfície reconstruída resultante é projetada em um mapa de profundidade 2D com resolução arbitrária. Experimentos conduzidos com diferentes subconjuntos do conjunto de dados do KITTI mostram uma melhora significativa produzida pela técnica proposta (esparso-para-contínuo), sem necessitar inserir informações extras durante a etapa de treinamento. / This work addresses the problem of single image depth estimation (SIDE), focusing on improving the quality of deep neural network predictions. In a supervised learning scenario, the quality of predictions is intrinsically related to the training labels, which guide the optimization process. For indoor scenes, structured-light-based depth sensors (e.g. Kinect) are able to provide dense, albeit short-range, depth maps. While for outdoor scenes, LiDARs are considered the standard sensor, which comparatively provide much sparser measurements, especially in areas further away. Rather than modifying the neural network architecture to deal with sparse depth maps, this work introduces a novel densification method for depth maps using the Hilbert Maps framework. A continuous occupancy map is produced based on 3D points from LiDAR scans, and the resulting reconstructed surface is projected into a 2D depth map with arbitrary resolution. Experiments conducted with various subsets of the KITTI dataset show a significant improvement produced by the proposed Sparse-to-Continuous technique, without the introduction of extra information into the training stage.

Modern automobiles and particularly those with off-road lineage possess subsystems that can be configured to better negotiate certain terrain types. Different terrain classes amount to different adherence (or surface grip) and compressibility properties that impact vehicle ma-noeuvrability and should therefore incur a tailored throttle response, suspension stiffness and so on. This thesis explores prospective terrain recognition for an anticipating terrain response driver assistance system. Recognition of terrain and road terrain is cast as a semantic segmen-tation task whereby forward driving images or point clouds are pre-segmented into atomic units and subsequently classified. Terrain classes are typically of amorphous spatial extent con-taining homogenous or granularly repetitive patterns. For this reason, colour and texture ap-pearance is the saliency of choice for monocular vision. In this work, colour, texture and sur-face saliency of atomic units are obtained with a bag-of-features approach. Five terrain classes are considered, namely grass, dirt, gravel, shrubs and tarmac. Since colour can be ambiguous among terrain classes such as dirt and gravel, several texture flavours are explored with scalar and structured output learning in a bid to devise an appropriate visual terrain saliency and predictor combination. Texture variants are obtained using local binary patters (LBP), filter responses (or textons) and dense key-point descriptors with daisy. Learning algorithms tested include support vector machine (SVM), random forest (RF) and logistic regression (LR) as scalar predictors while a conditional random field (CRF) is used for structured output learning. The latter encourages smooth labelling by incorporating the prior knowledge that neighbouring segments with similar saliency are likely segments of the same class. Once a suitable texture representation is devised the attention is shifted from monocular vision to stereo vision. Sur-face saliency from reconstructed point clouds can be used to enhance terrain recognition. Pre-vious superpixels span corresponding supervoxels in real world coordinates and two surface saliency variants are proposed and tested with all predictors: one using the height coordinates of point clouds and the other using fast point feature histograms (FPFH). Upon realisation that road recognition and terrain recognition can be assumed as equivalent problems in urban en-vironments, the top most accurate models consisting of CRFs are augmented with composi-tional high order pattern potentials (CHOPP). This leads to models that are able to strike a good balance between smooth local labelling and global road shape. For urban environments the label set is restricted to road and non-road (or equivalently tarmac and non-tarmac). Ex-periments are conducted using a proprietary terrain dataset and a public road evaluation da-taset.

O estudo teve como objetivos verificar em dois grupos de pacientes com visão monocular (grupo 1) e com visão binocular (grupo 2), a serem submetidos à cirurgia de catarata no Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, opiniões, expectativas e reações emocionais em relação ao problema ocular, à qualidade da visão e à cirurgia de catarata; influência da característica de apresentar visão mono ou binocular nas reações emocionais relacionadas à cirurgia de catarata. Foi realizado estudo transversal e comparativo, de forma consecutiva, por meio de questionário estruturado, aplicado por entrevista a pacientes, elaborado a partir de estudo exploratório e medidas acuidade visual e causa da perda visual. A amostra foi constituída por 96 indivíduos do grupo 1 (50,0% homens; 50,0% mulheres, com idade entre 41 e 91 anos, média 69,3 anos ± 10,4 anos) e 110, do grupo 2 (40,9% homens; 59,1% mulheres, com idade entre 40 e 89 anos, média 68,2 anos ± 10,2 anos). A maioria dos indivíduos de ambos os grupos apresentava baixa escolaridade. Não houve diferença estatisticamente significante entre os grupos em relação ao sexo (p = 0,191), à idade (p = 0,702) e à escolaridade (p = 0,245). Não exerciam atividade laboral 95,8% dos indivíduos do grupo 1 e 83,6%, do grupo 2 (p = 0,005) e 30,4% do grupo 1 mencionaram não ter possibilidade de trabalhar por causa da deficiência visual. Observou-se acuidade visual do olho a ser operado menor que 0,05 em 40,6% (grupo 1) e 33,6% (grupo 2), entre 0,25 e 0,05. Quase a totalidade dos indivíduos de ambos os grupos afirmou ter dificuldade para realização das atividades de vida diária e qualificou como insuficiente a respectiva acuidade visual; 71,9% dos entrevistados do grupo 1 e 71,6%, do grupo 2 mencionaram saber a causa da visão fraca; desses, 87,1% do grupo 1 e 83,3% do grupo 2 referiram a catarata como causa da baixa acuidade visual. No que se refere ao medo, 40,6% dos indivíduos do grupo 1 e 22,7%, do grupo 2, relataram ter medo do procedimento cirúrgico (p = 0,009). As causas de medo mais referidas foram: possibilidade de perder a visão; piorar a visão; sofrer alguma complicação na cirurgia; morrer durante a cirurgia. Os sentimentos mais preponderantes entre os grupos foram: satisfação por saber que a catarata pode ser operada e melhorar a visão, alívio por saber que vai ser operado, dúvida quanto a ter bom resultado, nervosismo. Referiram esperar que mudanças ocorressem na vida após a cirurgia 90,6% (grupo 1) e 84,6% (grupo 2). Quanto às atividades que esperavam realizar após a cirurgia mencionaram: realizar serviços de casa; ler; sair sozinho. Concluiu-se que: os indivíduos de ambos os grupos tiveram acesso à cirurgia de catarata com acuidade visual menor do que a idealmente indicada; os pacientes com visão monocular apresentaram acuidade visual significativamente menor em relação aos com visão binocular; a maioria dos entrevistados de ambos os grupos referiu dificuldades para realizar atividades cotidianas como conseqüência da baixa visão; os indivíduos com visão monocular referiram mais dúvida em relação aos resultados cirúrgicos do que os com visão binocular; muitos indivíduos de ambos os grupos desconheciam a causa da dificuldade visual ou a atribuíram a outra causa que não a catarata; indivíduos de ambos os grupos apontaram expectativas positivas em relação à reabilitação após a cirurgia. / The purpose of the study was to verify in two groups of patients with monocular vision (group 1) and with binocular vision (group 2) to be submitted to cataract surgery in Hospital das Clínicas, São Paulo University Medical School, opinions, expectances and emotional reactions related to the ocular problem, to the quality of vision and to cataract surgery, the influence of monocular or binocular vision in the emotional reactions related to cataract surgery. A transversal comparative and consecutive study was performed using a structured questionnaire applied by interview of patients. The questionnaire was elaborated from a previous exploratory study, the visual acuity and cause of the visual loss were evaluated. The sample was constituted by 96 persons of group 1 (50% males; 50% females, ages ranging from 41 to 91 years old; average 69,3 years ± 10,4 years) and 110 persons of group 2 (40,9% males; 59,1% females, ages ranging from 40 to 89 years old; average 68,2 years ± 10,2 years). The majority of persons of both groups presented low educational level. There was no statistically significant difference between the groups in relation to gender (p = 0,191), age (p = 0,702) and educational level (p = 0,245). No work activity was mentioned in 95,8% of the persons of group 1 and 83,6% of group 2 (p = 0,005) and 30,4% of group 1 informed the impossibility to work due the visual deficiency. It was observed that the visual acuity of the eye to be operated was less than 0,05 in 40,6% (group 1) and in 33,6% (group 2), presented visual acuity ranging from 0,05 to 0,25. Almost the totality of the persons of both groups informed difficulties to perform activities of daily life and qualified as insufficient their visual acuities; 71,9% of the patients of group 1 and 71,6% of group 2 informed to know the reason of low vision; among these, 87,1% of group 1 and 83,3% of group 2 mentioned cataract as the reason of low visual acuity. Concerning fear, 40,6% of patients of group 1 and 22,7% of group 2 informed about fear of the surgical procedure (p = 0,009). The causes of fear more frequently reported were: possibility of loss of vision; worsening of vision; complications during the surgical procedure and to die during the surgery. The more preponderant feelings in both groups were: satisfaction knowing that a cataract can be operated with improvement of vision, relief knowing that will be submitted to surgery, doubt about a good result, nervousness. Changes in the life after surgery were mentioned by 90,6% (group 1) and by 84,6% (group 2) of the persons. Housework activities, reading and moving around without help were the mentioned activities expected to be performed after surgery. It was concluded that the patients of both groups were submitted to cataract surgery with visual acuities less than the visual acuity ideally indicated; the patients with monocular vision showed visual acuities significantly less in relation to the patients with binocular vision; the majority of the patients of both groups mentioned difficulties to perform daily activities as a consequence of low vision; patients with monocular vision mentioned doubts in relation to the surgical results as compared with the patients with binocular vision; many patients of both groups did not know the cause of the visual difficulty or explained the visual difficulty by other cause than the cataract; patients of both groups were positively expectant in relation to the visual rehabilitation after the surgery.

Les travaux présentés dans ce manuscrit concernent le domaine de la localisation et la reconstruction 3D par vision artificielle. Dans ce contexte, la trajectoire d’une caméra et la structure3D de la scène filmée sont initialement estimées par des algorithmes linéaires puis optimisées par un algorithme non-linéaire, l’ajustement de faisceaux. Cette thèse présente tout d’abord une technique de recherche de l’amplitude de déplacement (recherche linéaire), ou line search pour les algorithmes de minimisation itérative. La technique proposée est non itérative et peut être rapidement implantée dans un ajustement de faisceaux traditionnel. Cette technique appelée recherche linéaire algébrique globale (G-ALS), ainsi que sa variante à deux dimensions (Two way-ALS), accélèrent la convergence de l’algorithme d’ajustement de faisceaux. L’approximation de l’erreur de reprojection par une distance algébrique rend possible le calcul analytique d’une amplitude de déplacement efficace (ou de deux pour la variante Two way-ALS), par la résolution d’un polynôme de degré 3 (G-ALS) ou 5 (Two way-ALS). Nos expérimentations sur des données simulées et réelles montrent que cette amplitude, optimale en distance algébrique, est performante en distance euclidienne, et permet de réduire le temps de convergence des minimisations. Une difficulté des algorithmes de localisation en temps réel par la vision (SLAM monoculaire) est que la trajectoire estimée est souvent affectée par des dérives : dérives d’orientation, de position et d’échelle. Puisque ces algorithmes sont incrémentaux, les erreurs et approximations sont cumulées tout au long de la trajectoire, et une dérive se forme sur la localisation globale. De plus, un système de localisation par vision peut toujours être ébloui ou utilisé dans des conditions qui ne permettent plus temporairement de calculer la localisation du système. Pour résoudre ces problèmes, nous proposons d’utiliser un capteur supplémentaire mesurant les déplacements de la caméra. Le type de capteur utilisé varie suivant l’application ciblée (un odomètre pour la localisation d’un véhicule, une centrale inertielle légère ou un système de navigation à guidage inertiel pour localiser une personne). Notre approche consiste à intégrer ces informations complémentaires directement dans l’ajustement de faisceaux, en ajoutant un terme de contrainte pondéré dans la fonction de coût. Nous évaluons trois méthodes permettant de sélectionner dynamiquement le coefficient de pondération et montrons que ces méthodes peuvent être employées dans un SLAM multi-capteur temps réel, avec différents types de contrainte, sur l’orientation ou sur la norme du déplacement de la caméra. La méthode est applicable pour tout autre terme de moindres carrés. Les expérimentations menées sur des séquences vidéo réelles montrent que cette technique d’ajustement de faisceaux contraint réduit les dérives observées avec les algorithmes de vision classiques. Ils améliorent ainsi la précision de la localisation globale du système. / The works presented in this manuscript are in the field of computer vision, and tackle the problem of real-time vision based localization and 3D reconstruction. In this context, the trajectory of a camera and the 3D structure of the filmed scene are initially estimated by linear algorithms and then optimized by a nonlinear algorithm, bundle adjustment. The thesis first presents a new technique of line search, dedicated to the nonlinear minimization algorithms used in Structure-from-Motion. The proposed technique is not iterative and can be quickly installed in traditional bundle adjustment frameworks. This technique, called Global Algebraic Line Search (G-ALS), and its two-dimensional variant (Two way-ALS), accelerate the convergence of the bundle adjustment algorithm. The approximation of the reprojection error by an algebraic distance enables the analytical calculation of an effective displacement amplitude (or two amplitudes for the Two way-ALS variant) by solving a degree 3 (G-ALS) or 5 (Two way-ALS) polynomial. Our experiments, conducted on simulated and real data, show that this amplitude, which is optimal for the algebraic distance, is also efficient for the Euclidean distance and reduces the convergence time of minimizations. One difficulty of real-time tracking algorithms (monocular SLAM) is that the estimated trajectory is often affected by drifts : on the absolute orientation, position and scale. Since these algorithms are incremental, errors and approximations are accumulated throughout the trajectory and cause global drifts. In addition, a tracking vision system can always be dazzled or used under conditions which prevented temporarily to calculate the location of the system. To solve these problems, we propose to use an additional sensor measuring the displacement of the camera. The type of sensor used will vary depending on the targeted application (an odometer for a vehicle, a lightweight inertial navigation system for a person). We propose to integrate this additional information directly into an extended bundle adjustment, by adding a constraint term in the weighted cost function. We evaluate three methods (based on machine learning or regularization) that dynamically select the weight associated to the constraint and show that these methods can be used in a real time multi-sensor SLAM, and validate them with different types of constraint on the orientation or on the scale. Experiments conducted on real video sequences show that this technique of constrained bundle adjustment reduces the drifts observed with the classical vision algorithms and improves the global accuracy of the positioning system.

Cette thèse traite de la détection et du suivi d'objets mobiles dans un environnement dynamique, en utilisant une caméra embarquée sur un robot mobile. Ce sujet représente encore un défi important car on exploite uniquement la vision mono-caméra pour le résoudre. Nous devons détecter les objets mobiles dans la scène par une analyse de leurs déplacements apparents dans les images, en excluant le mouvement propre de la caméra. Dans une première étape, nous proposons une analyse spatio-temporelle de la séquence d'images, sur la base du flot optique épars. La méthode de clustering a contrario permet le groupement des points dynamiques, sans information a priori sur le nombre de groupes à former et sans réglage de paramètres. La réussite de cette méthode réside dans une accumulation suffisante des données pour bien caractériser la position et la vitesse des points. Nous appelons temps de pistage, le temps nécessaire pour acquérir les images analysées pour bien caractériser les points. Nous avons développé une carte probabiliste afin de trouver les zones dans l'image qui ont les probabilités la plus grandes de contenir un objet mobile. Cette carte permet la sélection active de nouveaux points près des régions détectées précédemment en permettant d'élargir la taille de ces régions. Dans la deuxième étape nous mettons en oeuvre une approche itérative pour exécuter détection, clustering et suivi sur des séquences d'images acquises depuis une caméra fixe en intérieur et en extérieur. Un objet est représenté par un contour actif qui est mis à jour de sorte que le modèle initial reste à l'intérieur du contour. Finalement nous présentons des résultats expérimentaux sur des images acquises depuis une caméra embarquée sur un robot mobile se déplaçant dans un environnement extérieur avec des objets mobiles rigides et nonrigides. Nous montrons que la méthode est utilisable pour détecter des obstacles pendant la navigation dans un environnement inconnu a priori, d'abord pour des faibles vitesses, puis pour des vitesses plus réalistes après compensation du mouvement propre du robot dans les images.

Les travaux présentés ici concernent le domaine de la localisation de véhicule par vision artificielle. Dans ce contexte, la trajectoire d’une caméra et la structure3D de la scène filmée sont estimées par une méthode d’odométrie visuelle monoculaire basée sur l’ajustement de faisceaux local. Les contributions de cette thèse sont plusieurs améliorations de cette méthode. L’incertitude associée à la position estimée n’est pas fournie par la méthode d’ajustement de faisceaux local. C’est pourtant une information indispensable pour pouvoir utiliser cette position, notamment dans un système de fusion multi-sensoriel. Une étude de la propagation d’incertitude pour cette méthode d’odométrie visuelle a donc été effectuée pour obtenir un calcul d’incertitude temps réel et représentant l’erreur de manière absolue (dans le repère du début de la trajectoire). Sur de longues séquences (plusieurs kilomètres), les méthodes monoculaires de localisation sont connues pour présenter des dérives importantes dues principalement à la dérive du facteur d’échelle (non observable). Pour réduire cette dérive et améliorer la qualité de la position fournie, deux méthodes de fusion ont été développées. Ces deux améliorations permettent de rendre cette méthode monoculaire exploitable dans le cadre automobile sur de grandes distances tout en conservant les critères de temps réel nécessaire dans ce type d’application. De plus, notre approche montre l’intérêt de disposer des incertitudes et ainsi de tirer parti de l’information fournie par d’autres capteurs. / The present work is about localisation of vehicle using computer vision methods. In this context, the camera trajectory and the 3D structure of the scene is estimated by a monocular visual odometry method based on local bundle adjustment. This thesis contributions are some improvements of this method. The uncertainty of the estimated position was not provided by the local bundle adjustment method. Indeed, this uncertainty is crucial in a multi-sensorial fusion system to use optimally the estimated position. A study of the uncertainty propagation in this visual odometry method has been done and an uncertainty calculus method has been designed to comply with real time performance. By the way, monocular visual localisation methods are known to have serious drift issues on long trajectories (some kilometers). This error mainly comes from bad propagation of the scale factor. To limit this drift and improve the quality of the given position, we proposed two data fusion methods between an odometer and the visual method. Finally, the two improvements presented here allow us to use visual localisation method in real urban environment on long trajectories under real time constraints.

O estudo teve como objetivos verificar em dois grupos de pacientes com visão monocular (grupo 1) e com visão binocular (grupo 2), a serem submetidos à cirurgia de catarata no Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, opiniões, expectativas e reações emocionais em relação ao problema ocular, à qualidade da visão e à cirurgia de catarata; influência da característica de apresentar visão mono ou binocular nas reações emocionais relacionadas à cirurgia de catarata. Foi realizado estudo transversal e comparativo, de forma consecutiva, por meio de questionário estruturado, aplicado por entrevista a pacientes, elaborado a partir de estudo exploratório e medidas acuidade visual e causa da perda visual. A amostra foi constituída por 96 indivíduos do grupo 1 (50,0% homens; 50,0% mulheres, com idade entre 41 e 91 anos, média 69,3 anos ± 10,4 anos) e 110, do grupo 2 (40,9% homens; 59,1% mulheres, com idade entre 40 e 89 anos, média 68,2 anos ± 10,2 anos). A maioria dos indivíduos de ambos os grupos apresentava baixa escolaridade. Não houve diferença estatisticamente significante entre os grupos em relação ao sexo (p = 0,191), à idade (p = 0,702) e à escolaridade (p = 0,245). Não exerciam atividade laboral 95,8% dos indivíduos do grupo 1 e 83,6%, do grupo 2 (p = 0,005) e 30,4% do grupo 1 mencionaram não ter possibilidade de trabalhar por causa da deficiência visual. Observou-se acuidade visual do olho a ser operado menor que 0,05 em 40,6% (grupo 1) e 33,6% (grupo 2), entre 0,25 e 0,05. Quase a totalidade dos indivíduos de ambos os grupos afirmou ter dificuldade para realização das atividades de vida diária e qualificou como insuficiente a respectiva acuidade visual; 71,9% dos entrevistados do grupo 1 e 71,6%, do grupo 2 mencionaram saber a causa da visão fraca; desses, 87,1% do grupo 1 e 83,3% do grupo 2 referiram a catarata como causa da baixa acuidade visual. No que se refere ao medo, 40,6% dos indivíduos do grupo 1 e 22,7%, do grupo 2, relataram ter medo do procedimento cirúrgico (p = 0,009). As causas de medo mais referidas foram: possibilidade de perder a visão; piorar a visão; sofrer alguma complicação na cirurgia; morrer durante a cirurgia. Os sentimentos mais preponderantes entre os grupos foram: satisfação por saber que a catarata pode ser operada e melhorar a visão, alívio por saber que vai ser operado, dúvida quanto a ter bom resultado, nervosismo. Referiram esperar que mudanças ocorressem na vida após a cirurgia 90,6% (grupo 1) e 84,6% (grupo 2). Quanto às atividades que esperavam realizar após a cirurgia mencionaram: realizar serviços de casa; ler; sair sozinho. Concluiu-se que: os indivíduos de ambos os grupos tiveram acesso à cirurgia de catarata com acuidade visual menor do que a idealmente indicada; os pacientes com visão monocular apresentaram acuidade visual significativamente menor em relação aos com visão binocular; a maioria dos entrevistados de ambos os grupos referiu dificuldades para realizar atividades cotidianas como conseqüência da baixa visão; os indivíduos com visão monocular referiram mais dúvida em relação aos resultados cirúrgicos do que os com visão binocular; muitos indivíduos de ambos os grupos desconheciam a causa da dificuldade visual ou a atribuíram a outra causa que não a catarata; indivíduos de ambos os grupos apontaram expectativas positivas em relação à reabilitação após a cirurgia. / The purpose of the study was to verify in two groups of patients with monocular vision (group 1) and with binocular vision (group 2) to be submitted to cataract surgery in Hospital das Clínicas, São Paulo University Medical School, opinions, expectances and emotional reactions related to the ocular problem, to the quality of vision and to cataract surgery, the influence of monocular or binocular vision in the emotional reactions related to cataract surgery. A transversal comparative and consecutive study was performed using a structured questionnaire applied by interview of patients. The questionnaire was elaborated from a previous exploratory study, the visual acuity and cause of the visual loss were evaluated. The sample was constituted by 96 persons of group 1 (50% males; 50% females, ages ranging from 41 to 91 years old; average 69,3 years ± 10,4 years) and 110 persons of group 2 (40,9% males; 59,1% females, ages ranging from 40 to 89 years old; average 68,2 years ± 10,2 years). The majority of persons of both groups presented low educational level. There was no statistically significant difference between the groups in relation to gender (p = 0,191), age (p = 0,702) and educational level (p = 0,245). No work activity was mentioned in 95,8% of the persons of group 1 and 83,6% of group 2 (p = 0,005) and 30,4% of group 1 informed the impossibility to work due the visual deficiency. It was observed that the visual acuity of the eye to be operated was less than 0,05 in 40,6% (group 1) and in 33,6% (group 2), presented visual acuity ranging from 0,05 to 0,25. Almost the totality of the persons of both groups informed difficulties to perform activities of daily life and qualified as insufficient their visual acuities; 71,9% of the patients of group 1 and 71,6% of group 2 informed to know the reason of low vision; among these, 87,1% of group 1 and 83,3% of group 2 mentioned cataract as the reason of low visual acuity. Concerning fear, 40,6% of patients of group 1 and 22,7% of group 2 informed about fear of the surgical procedure (p = 0,009). The causes of fear more frequently reported were: possibility of loss of vision; worsening of vision; complications during the surgical procedure and to die during the surgery. The more preponderant feelings in both groups were: satisfaction knowing that a cataract can be operated with improvement of vision, relief knowing that will be submitted to surgery, doubt about a good result, nervousness. Changes in the life after surgery were mentioned by 90,6% (group 1) and by 84,6% (group 2) of the persons. Housework activities, reading and moving around without help were the mentioned activities expected to be performed after surgery. It was concluded that the patients of both groups were submitted to cataract surgery with visual acuities less than the visual acuity ideally indicated; the patients with monocular vision showed visual acuities significantly less in relation to the patients with binocular vision; the majority of the patients of both groups mentioned difficulties to perform daily activities as a consequence of low vision; patients with monocular vision mentioned doubts in relation to the surgical results as compared with the patients with binocular vision; many patients of both groups did not know the cause of the visual difficulty or explained the visual difficulty by other cause than the cataract; patients of both groups were positively expectant in relation to the visual rehabilitation after the surgery.