In recent years, the design, fabrication, and control of robotic systems inspired by biology has gained renewed attention due to the potential improvements in efficiency, maneuverability, and adaptability with which animals interact with their environments. Motion studies of biological systems such as humans, fish, insects, birds and bats are often used as a basis for robotic system design. Often, these studies are conducted by recording natural motions of the system of interest using a few high-resolution, high-speed cameras. Such equipment enables the use of standard methods for corresponding features and producing three-dimensional reconstructions of motion. These studies are then interpreted by a designer for kinematic, dynamic, and control systems design of a robotic system. This methodology generates impressive robotic systems which imitate their biological counter parts. However, the equipment used to study motion is expensive and designer interpretation of kinematics data requires substantial time and talent, can be difficult to identify correctly, and often yields kinematic inconsistencies between the robot and biology. To remedy these issues, this dissertation leverages the use of low-cost, low-speed, low-resolution cameras for tracking bat flight and presents a methodology for automatically learning physical geometry which restricts robotic joints to a motion submanifold identified from motion capture data. To this end, we present a spatially recursive state estimator which incorporates inboard state correction for producing accurate state estimates of bat flight. Using these state estimates, we construct a Gaussian process dynamic model (GPDM) of bat flight which is the first nonlinear dimensionality reduction of flapping flight in bats. Additionally, we formulate a novel method for learning robotic joint geometry directly from the experimental observations. To do this, we leverage recent developments in learning theory which derive analytical-empirical potential energy fields for identifying an underlying motion submanifold. We use these energy fields to optimize a compliant structure around a single degree-of-freedom elbow joint and to design rigid structures around spherical joints for an entire bat wing. Validation experiments show that the learned joint geometry restricts the motion of the joints to those observed during experiment. / Ph. D. / In recent years, robots modeled after biological systems have become increasingly prevalent. Such robots are often designed based on motion capture experiments of the animal they aim to imitate. The motion studies are typically conducted using commercial motion capture systems such as ViconTM or OptiTrackTM or a few high-speed, high-resolution cameras such as those marketed by PhotronTM or PhantomTM. These systems allow for automated processing of video sequences into three-dimensional reconstructions of the biological motion using standard image processing and state estimation techniques. The motion data is then used to drive robotic system designs such as the SonyTM AiboTM dog and the Boston Dynamics Atlas humanoid robot. While the motion capture data forms a basis for these impressive robots, the progression from data to robotic system is neither algorithmic nor rigorous and requires substantial interpretation by a human. In contrast, this dissertation presents a novel experimental and computational framework which uses low-speed, low-resolution cameras for capturing the complex motion of bats in flight and introduces a methodology which uses the motion capture data to directly design geometry which restricts the motion of joints to the motions observed in experiment. The advantage of our method is that the designer only needs to specify a general joint geometry such as a ball or pin joint, and geometry which restricts the motion is automatically identified. To do this, we learn an energy field over the set of kinematic configurations observed during experiment. This energy field “pushes” system trajectories towards those experimentally observed trajectories. We then learn compliant or rigid geometry which approximates this energy field to physically restrict the range of motion of the joint. We validate our method by fabricating joint geometry designed using both these approaches and present experiments which confirm that the reachable set of the joint is approximately the same as the set of configurations observed during experiments.

L'ablation des tissus par hyperthermie locale guidée par IRM est une technique prometteuse pour le traitement du cancer et des arythmies cardiaques. L'IRM permet d'extraire en temps réel des informations anatomiques et thermiques des tissus. Cette thèse a pour objectif d'améliorer et d'étendre la méthodologie existante pour des interventions sur des organes mobiles comme le rein, le foie et le coeur. La première partie a été consacrée à l'introduction de l'imagerie rapide (jusqu'à 10-15 Hz) pour le guidage de l'intervention par IRM en temps réel. L'utilisation de cartes graphiques (GPGPU) a permis une accélération des calculs afin de satisfaire la contrainte de temps réel. Une précision, de l'ordre de 1°C dans les organes abdominaux et de 2-3°C dans le coeur, a été obtenue. Basé sur ces avancées, de nouveaux développements méthodologiques ont été proposés dans une seconde partie de cette thèse. L'estimation du mouvement basée sur une approche variationnelle a été améliorée pour gérer la présence de structures non persistantes et de fortes variations d'intensité dans les images. Un critère pour évaluer la qualité du mouvement estimé a été proposé et utilisé pour auto-calibrer notre algorithme d'estimation du mouvement. La méthode de correction des artefacts de thermométrie liés au mouvement, jusqu'ici restreinte aux mouvements périodiques, a été étendue à la gestion de mouvements spontanés. Enfin, un nouveau filtre temporel a été développé pour la réduction du bruit sur les cartographies de température. La procédure interventionnelle apparaît maintenant suffisamment mature pour le traitement des organes abdominaux et pour le transfert vers la clinique. Concernant le traitement des arythmies cardiaques, les méthodes ont été évaluées sur des sujets sains et dans le ventricule gauche. Par conséquent, la faisabilité de l'intervention dans les oreillettes mais aussi en présence d'arythmie devra être abordée. / MR-guided thermal ablation is a promising technique for the treatment of cancer and atrial fibrillation. MRI provides both anatomical and temperature information. The objective of this thesis is to extend and improve existing techniques for such interventions in mobile organs such as the kidney, the liver and the heart. A first part of this work focuses on the use of fast MRI (up to 10-15 Hz) for guiding the intervention in real time. This study demonstrated the potential of GPGPU programming as a solution to guarantee the real time condition for both MR-reconstruction and MR-thermometry. A precision in the range of 1°C and 2-3°C was obtained in abdominal organs and in the heart, respectively. Based on these advances, new methodological developments have been carried out in a second part of this thesis. New variational approaches have proposed to address the problem of motion estimation in presence of structures appearing transient and high intensity variations in images. A novel quality criterion to assess the motion estimation is proposed and used to autocalibrate our motion estimation algorithm. The correction of motion related magnetic susceptibility variation was extended to treat the special case of spontaneous motion. Finally, a novel temporal filter is proposed to reduce the noise of MR-thermometry measurements while controlling the bias introduced by the filtering process. As a conclusion, all main obstacles for MR-guided HIFU-ablation of abdominal organs have been addressed in in-vivo and ex-vivo studies, therefore clinical studies will now be realized. However, although promising results have been obtained for MR-guided RF-ablation in the heart, its feasibility in the atrium and in presence of arrhythmia still remains to be investigated.

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Recentemente surgiram dispositivos sensores de profundidade capazes de capturar textura e geometria de uma cena em tempo real. Com isso, diversas técnicas de Visão Computacional, que antes eram aplicadas apenas a texturas, agora são passíveis de uma reformulação, visando o uso também da geometria. Ao mesmo tempo em que tais algoritmos, tirando vantagem dessa nova tecnologia, podem ser acelerados ou tornarem-se mais robustos, surgem igualmente diversos novos desafios e problemas interessantes a serem enfrentados. Como exemplo desses dispositivos podemos citar o do Projeto Vídeo 4D, do IMPA, e o Kinect (TM), da Microsoft. Esses equipamentos fornecem imagens que vêm sendo chamadas de RGBD, fazendo referência aos três canais de cores e ao canal adicional de profundidade (com a letra \'D\' vindo do termo depth, profundidade em inglês). A pesquisa descrita nesta tese apresenta uma nova abordagem não-supervisionada para a estimação de movimento a partir de vídeos compostos por imagens RGBD. Esse é um passo intermediário necessário para a identificação de componentes rígidos de um objeto articulado. Nosso método faz uso da técnica de casamento inexato (homomorfismo) entre grafos para encontrar grupos de pixels (blocos) que se movem para um mesmo sentido em quadros consecutivos de um vídeo. Com o intuito de escolher o melhor casamento para cada bloco, é minimizada uma função custo que leva em conta distâncias tanto no espaço de cores RGB quanto no XYZ (espaço tridimensional do mundo). A contribuição metodológica consiste justamente na manipulação dos dados de profundidade fornecidos pelos novos dispositivos de captura, de modo que tais dados passem a integrar o vetor de características que representa cada bloco nos grafos a serem casados. Nosso método não usa quadros de referência para inicialização e é aplicável a qualquer vídeo que contenha movimento paramétrico por partes. Para blocos cujas dimensões causem uma relativa diminuição na resolução das imagens, nossa aplicação roda em tempo real. Para validar a metodologia proposta, são apresentados resultados envolvendo diversas classes de objetos com diferentes tipos de movimento, tais como vídeos de pessoas caminhando, os movimento de um braço e um casal de dançarinos de samba de gafieira. Também são apresentados os avanços obtidos na modelagem de um sistema de vídeo 4D orientado a objetos, o qual norteia o desenvolvimento de diversas aplicações a serem desenvolvidas na continuação deste trabalho. / Depth-sensing devices have arised recently, allowing real-time scene texture and depth capture. As a result, many computer vision techniques, primarily applied only to textures, now can be reformulated using additional properties like the geometry. At the same time that these algorithms, making use of this new technology, can be accelerated or be made more robust, new interesting challenges and problems to be confronted are appearing. Examples of such devices include the 4D Video Project, from IMPA, and Kinect (TM) from Microsoft. These devices offer the so called RGBD images, being related to the three color channels and to the additional depth channel. The research described on this thesis presents a new non-supervised approach to estimate motion from videos composed by RGBD images. This is an intermediary and necessary step to identify the rigid components of an articulated object. Our method uses the technique of inexact graph matching (homomorphism) to find groups of pixels (patches) that move to the same direction in subsequent video frames. In order to choose the best matching for each patch, we minimize a cost function that accounts for distances on RGB color and XYZ (tridimensional world coordinates) spaces. The methodological contribution consists on depth data manipulation given by the new capture devices, such that these data become components of the feature vector that represents each patch on graphs to be matched. Our method does not use reference frames in order to be initialized and it can be applied to any video that contains piecewise parametric motion. For patches which allow a relative decrease on images resolution, our application runs in real-time. In order to validate the proposed methodology, we present results involving object classes with different movement kinds, such as videos with walking people, the motions of an arm and a couple of samba dancers. We also present the advances obtained on modeling an object oriented 4D video system, which guide a development of different applications to be developed as future work.

Câmeras embarcadas em sistemas robóticos móveis com sensoriamento visual geralmente são afetadas pelo movimento de seu suporte quando é necessária a aquisição de imagens com alta confiabilidade. Algumas câmeras disponíveis no mercado já estão equipadas com sistemas de estabilização de imagens, implementados nas lentes da câmera ou no sensor de imagem. Esses sistemas são relativamente caros para serem instalados em sistemas robóticos móveis aéreos ou terrestres de pequeno porte. Outro conceito que tem sido utilizado para alcançar a estabilização consiste em adotar sensores inerciais, algoritmos de visão computacional e aplicação de filtros digitais para estimativa e suavização de movimento. Esta dissertação tem por finalidade apresentar um sistema de estabilização digital de vídeo em conjunto com um acelerômetro para detectar movimentos da câmera. Considera-se que a câmera está instalada sobre plataforma instável ou em veículo em movimento, assim, utiliza-se filtragem robusta para minimizar o efeito da vibração sobre a câmera. Vários experimentos são realizados adicionando vibração em vídeo por meio de simulações em computador. Considera-se também experimentos em ambiente real com a câmera montada em um suporte dentro de um veículo em movimento. A principal contribuição deste trabalho é a realização de um estudo comparativo para analisar a vantagem de se usar uma abordagem robusta entre os métodos de filtragem comumente utilizados em sistemas de estabilização de vídeo. / Embedded cameras in robotic systems usually are susceptible to movements of your basis. The measurements can be affected mainly when they should obtain high performance in actual applications. Although some cameras available on the market are already equipped with an optical image stabilization system, implemented either in the camera lenses or in the image sensor. They are usually expensive to be installed into small aerial or land robotic systems. This dissertation presents a video stabilization system coupled with an accelerometer for motion detection at an unstable platform. It is embedded in a vehicle. Robust filtering is used to minimize vibration effects on the camera. Several experiments were performed, adding either vibrations via computer simulations and taking images from the camera with the vehicle moving. The main contribution of this work is the accomplishment of a comparative study to analyse the advantages of applying a robust approach among others filtering methods that frequently are used to video stabilizing systems.

Les travaux présentés dans ce manuscrit s’inscrivent dans un projet de thermométrie cardiaque par IRM. L’objectif de cette approche est de monitorer en temps réel le traitement des arythmies cardiaques par ablation thermique. Dans la chaine de traitement utilisée, des méthodes de recalage d’images doivent être implémentées afin d’assurer un suivi exploitable de l’ablation. En effet, les mouvements des différents organes localisés dans la (les) coupe(s) d’imagerie ont un impact sur la précision de la thermométrie IRM. Les méthodes d’estimation de mouvement doivent cependant être robustes aux différents artefacts (faible SNR, flux sanguin dans les cavités cardiaques, etc.) et utilisables en pseudo temps réel (10 images/seconde). Les travaux présentés dans ce manuscrit se concentrent sur la robustesse des méthodes de recalage d’images. Tout d’abord, le bruit inhérent aux images IRM a été intégré à l’estimation de mouvement. Ceci permet de pondérer localement les voxels de l’image dans le calcul du déplacement. Ensuite, une annulation numérique du signal chaotique du sang à l’intérieur du ventricule gauche est proposée via une segmentation semi-automatique de celuici à base de modèle déformable. Un nouveau terme, issu de la probabilité d’appartenir à ce ventricule, a été ajouté dans l’algorithme de contour actif. Les méthodes proposées apportent une amélioration de la qualité de l’estimation du mouvement. Elles sont adaptées à la chaine de traitement de thermométrie afin de les rendre automatiques dans la phase d’ablation thermique de la procédure. De plus, ces méthodes répondent aux contraintes de temps réel de la thermométrie IRM / The works presented in the manuscript are incorporated within the framework of cardiac MR thermometry. The aim of this approach is to monitor in real time the treatment of arrhy²thmias by thermal ablation. In the pipeline used in thermometry, image registration methods have to be inserted to unsure a reliable monitoring of the treatment. Indeed, motions of the different organs present in the acquisition slices have an impact on the accuracy of the MR thermometry. Furthermore, image registration has to be robust to artefacts (low SNR, blood flow in the heart cavities…) and has to be used in real time (10 images/second). The works presented in this manuscript focuses on the robustness of the image registration methods. First, the MR images inherent noise is integrated to the motion estimation. It enables the local weighting of the image’s voxels in the computing of the displacement. Then, a numerical cancelation of the chaotic blood flow signal within the left ventricle through a semi-automatic segmentation is proposed. A new term based on the probability to belong to this ventricle is added to the active contour algorithm. The proposed methods improved the quality of the motion estimation. They are adapted to the thermometry pipeline to make them automatic in the thermal ablation phase of the procedure. They are also compatible with the real-time aspect of MR thermometry.

<p>This thesis describes and evaluates a number of algorithms for reducing fixed pattern noise in image sequences. Fixed pattern noise is the dominantnoise component for many infrared detector systems, perceived as a superimposed pattern that is approximately constant for all image frames. </p><p>Primarily, methods based on estimation of the movement between individual image frames are studied. Using scene-matching techniques, global motion between frames can be successfully registered with sub-pixel accuracy. This allows each scene pixel to be traced along a path of individual detector elements. Assuming a static scene, differences in pixel intensities are caused by fixed pattern noise that can be estimated and removed. </p><p>The algorithms have been tested by using real image data from existing infrared imaging systems with good results. The tests include both a two-dimensional focal plane array detector and a linear scanning one-dimensional detector, in different scene conditions.</p>

This thesis describes and evaluates a number of algorithms for reducing fixed pattern noise in image sequences. Fixed pattern noise is the dominantnoise component for many infrared detector systems, perceived as a superimposed pattern that is approximately constant for all image frames. Primarily, methods based on estimation of the movement between individual image frames are studied. Using scene-matching techniques, global motion between frames can be successfully registered with sub-pixel accuracy. This allows each scene pixel to be traced along a path of individual detector elements. Assuming a static scene, differences in pixel intensities are caused by fixed pattern noise that can be estimated and removed. The algorithms have been tested by using real image data from existing infrared imaging systems with good results. The tests include both a two-dimensional focal plane array detector and a linear scanning one-dimensional detector, in different scene conditions.

In today's industry 3D cameras are often used to inspect products. The camera produces both a 3D model and an intensity image by capturing a series of profiles of the object using laser triangulation. In many of these setups a physical encoder is attached to, for example, the conveyor belt that the product is travelling on. The encoder is used to get an accurate reading of the speed that the product has when it passes through the laser. Without this, the output image from the camera can be distorted due to a variation in velocity. In this master thesis a method for integrating the functionality of this physical encoder into the software of the camera is proposed. The object is scanned together with a pattern, with the help of this pattern the object can be restored to its original proportions. / I dagens industri används ofta 3D-kameror för att inspektera produkter. Kameran producerar en 3D-modell samt en intensitetsbild genom att sätta ihop en serie av profilbilder av objektet som erhålls genom lasertriangulering. I många av dessa uppställningar används en fysisk encoder som återspeglar hastigheten på till exempel transportbandet som produkten ligger på. Utan den här encodern kan bilden som kameran fångar bli förvrängd på grund av hastighetsvariationer. I det här examensarbetet presenteras en metod för att integrera funktionaliteten av encodern in i kamerans mjukvara. För att göra detta krävs att ett mönster placeras längs med objektet som ska bli skannat. Mönstret återfinns i bilden fångad av kameran och med hjälp av detta mönster kan hastigheten bestämmas och objektets korrekta proportioner återställas.

Algorithm-Based Efficient Approaches for Motion Estimation Systems Teahyung Lee 121 pages Directed by Dr. David V. Anderson This research addresses algorithms for efficient motion estimation systems. With the growth of wireless video system market, such as mobile imaging, digital still and video cameras, and video sensor network, low-power consumption is increasingly desirable for embedded video systems. Motion estimation typically needs considerable computations and is the basic block for many video applications. To implement low-power video systems using embedded devices and sensors, a CMOS imager has been developed that allows low-power computations on the focal plane. In this dissertation efficient motion estimation algorithms are presented to complement this platform. In the first part of dissertation we propose two algorithms regarding gradient-based optical flow estimation (OFE) to reduce computational complexity with high performance. The first is a checkerboard-type filtering (CBTF) algorithm for prefiltering and spatiotemporal derivative calculations. Another one is spatially recursive OFE frameworks using recursive LS (RLS) and/or matrix refinement to reduce the computational complexity for solving linear system of derivative values of image intensity in least-squares (LS)-OFE. From simulation results, CBTF and spatially recursive OFE show improved computational efficiency compared to conventional approaches with higher or similar performance. In the second part of dissertation we propose a new algorithm for video coding application to improve motion estimation and compensation performance in the wavelet domain. This new algorithm is for wavelet-based multi-resolution motion estimation (MRME) using temporal aliasing detection (TAD) to enhance rate-distortion (RD) performance under temporal aliasing noise. This technique gives competitive or better performance in terms of RD compared to conventional MRME and MRME with motion vector prediction through median filtering.