A significant amount of research in the field of stereo vision has been published in the past decade. Considerable progress has been made in improving accuracy of results as well as achieving real-time performance in obtaining those results. Although much of the literature does not address it, many applications are sensitive to the tradeoff between accuracy and speed that exists among stereo vision algorithms. Overall, this work aims to organize existing efforts and encourage new ones in the development of stereo vision algorithms for resource limited systems. It does this through a review of the status quo as well as providing both software and hardware designs of new stereo vision algorithms that offer an efficient tradeoff between speed and accuracy. A comprehensive review and analysis of stereo vision algorithms is provided with specific emphasis on real-time performance and suitability for resource limited systems. An attempt has been made to compile and present accuracy and runtime performance data for all stereo vision algorithms developed in the past decade. The tradeoff in accuracy that is typically made to achieve real-time performance is examined with an example of an existing highly accurate stereo vision that is modified to see how much speedup can be achieved. Two new stereo vision algorithms, GA Spline and Profile Shape Matching, are presented with a hardware design of the latter also being provided, making Profile Shape Matching available to both embedded processor-based and programmable hardware-based resource limited systems.

This thesis introduces methods for adding user-guided depth-aware effects to images captured with a consumer-grade stereo camera with minimal user interaction. In particular, we present methods for highlighted depth-of-field, haze, depth-of-field, and image relighting. Unlike many prior methods for adding such effects, we do not assume prior scene models or require extensive user guidance to create such models, nor do we assume multiple input images. We also do not require specialized camera rigs or other equipment such as light-field camera arrays, active lighting, etc. Instead, we use only an easily portable and affordable consumer-grade stereo camera. The depth is calculated from a stereo image pair using an extended version of PatchMatch Stereo designed to compute not only image disparities but also normals for visible surfaces. We also introduce a pipeline for rendering multiple effects in the order they would occur physically. Each can be added, removed, or adjusted in the pipeline without having to reapply subsequent effects. Individually or in combination, these effects can be used to enhance the sense of depth or structure in images and provide increased artistic control. Our interface also allows editing the stereo pair together in a fashion that preserves stereo consistency, or the effects can be applied to a single image only, thus leveraging the advantages of stereo acquisition even to produce a single photograph.

This thesis covers the topic of depth- assisted Structure from Motion (SfM). When performing classic SfM, the goal is to reconstruct a 3D scene using only a set of unstructured RGB images. What is attempted to be achieved in this thesis is adding the depth dimension to the problem formulation, and consequently create a system that can receive a set of RGBD images. The problem has been addressed by modifying an already existing SfM pipeline and in particular, its Bundle Adjustment (BA) process. Comparisons between the modified framework and the baseline framework resulted in conclusions regarding the impact of the modifications. The results show mainly two things. First of all, the accuracy of the framework is increased in most situations. The difference is the most significant when the captured scene only is covered from a small sector. However, noisy data can cause the modified pipeline to decrease in performance. Secondly, the run time of the framework is significantly reduced. A discussion of how to modify other parts of the pipeline is covered in the conclusion of the report. / Följande examensarbete behandlar ämnet djupassisterad Struktur genom Rörelse (eng. SfM). Vid klassisk SfM är målet att återskapa en 3D scen, endast med hjälp av en sekvens av oordnade RGB bilder. I djupassiterad SfM adderas djupinformationen till problemformulering och följaktligen har ett system som kan motta RGBD bilder skapats. Problemet har lösts genom att modifiera en befintlig SfM- mjukvara och mer specifikt dess Buntjustering (eng. BA). Resultatet från den modifierade mjukvaran jämförs med resultatet av originalutgåvan för att dra slutsatser rådande modifikationens påverkan på prestandan. Resultaten visar huvudsakligen två saker. Först och främst, den modifierade mjukvaran producerar resultat med högre noggrannhet i de allra flesta fall. Skillnaden är som allra störst när bilderna är tagna från endast en liten sektor som omringar scenen. Data med brus kan dock försämra systemets prestanda aningen jämfört med orginalsystemet. För det andra, så minskar exekutionstiden betydligt. Slutligen diskuteras hur mjukvaran kan vidareutvecklas för att ytterligare förbättra resultaten.

In den letzten Jahren sind immer mehr erschwingliche Kamera-Sensoren mit einer zunehmenden Vielfalt optischer Abbildungsfunktionen verfügbar geworden. Low-Cost-Optiken können aufgrund höherer Toleranzen und unterschiedlicher optischer Materialien von der gewünschten Lochkamera Metrik abweichen. Weitwinkel- und Fischaugenobjektive, verzerrende katadioptrische Objektive (spiegelnd und refraktiv) und andere ungewöhnliche Objektive weichen von der Annahme des Modells einer Lochkamera mit einer Brennweite ab. Actionkameras können die gesamte Umgebung mit zwei Objektiven abbilden, diese entsprechen meist nicht mehr dem Lochkameramodell. Kameras werden auch für Messaufgaben hinter zusätzlichen optischen Elementen eingesetzt. Die vorliegende Arbeit erweitert die ersten Erkenntnisse im Bereich der differenzierbaren (glatten) Kameramodelle ohne Einschränkungen. Viele existierende Modelle sind auf bestimmte Objektivtypen spezialisiert. In dieser Arbeit werden mehrere solcher allgemeinen Modelle eingeführt, ohne dass eine global feste Brennweite und spezielle Anforderungen an die Symmetrie der Abbildung erforderlich sind. Eine Einführung alternativer Fehlermetriken im Objektraum bringt auch enorme Rechenvorteile, da eine Abbildungsrichtung analytisch berechnet und viele der Berechnungsergebnisse konstant gehalten werden können. Zur Initialisierung solcher Modelle wird in dieser Arbeit eine generische lineare Kamera vorgestellt. Das wesentliche Merkmal dabei ist eine künstliche Transformation in höhere Dimensionen, welche mit linearen Verfahren weiterverwendet werden. Sie modellieren bereits nichtlineare Verzerrungen und Asymmetrien. Eine Multikamera-Kalibrierungssoftware wird ebenfalls beschrieben und implementiert. Das Ergebnis der Arbeit ist ein theoretischer Rahmen für glatte Kameramodelle im Objektraum selbst – anstelle der Abbildung in den Bildraum – mit mehreren konkreten Modellvorschlägen, Implementierungen und dem angepassten und erweiterten Kalibrierungsprozess. / In recent years, more and more affordable camera sensors with an increasing variety of optical imaging features have become available. Low-cost optics may deviate from the desired pinhole metric due to higher tolerances and different optical materials. Wide-angle and fisheye lenses, distorting catadioptric lenses (specular and refractive) and other unusual lenses deviate from the single focal pinhole camera model assumption, which is sometimes intentional. Action cameras can map the entire environment using two lenses, these usually no longer correspond to the pinhole camera model. Cameras are also used for measuring tasks behind additional optical elements – with unforeseeable deviations in the line of sight. The present work expands the first findings in the field of differentiable (smooth) camera models without constraints. Many existing models specialise in certain types of lenses. In this work, several such general models are introduced without requiring fixed global focal length and symmetry requirements. An introduction of alternative error metrics in the object space also gives enormous computational advantages, since one imaging direction can be calculated analytically and many of the calculation results can be kept constant. For the generation of meaningful starting values of such models, this work introduces a generic linear camera. The essential feature of is an artificial transformation into higher dimensions. These transformed coordinates can then continue to be used with linear methods. They already model non-linear distortions and asymmetries. A multi-camera calibration software that efficiently implements these models is also described and implemented. The result of the work is a theoretical framework for smooth camera models in the object space itself - instead of the established mapping into the image space - with several concrete model proposals, implementations and the adapted and extended calibration process.

ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada / To monitor ocean resources and environment, we develop an ocean stereo telemetry system built on a PC104 industrial control computer, which is carried by a buoy on the ocean. All monitoring instruments communicate with the computer by six serial ports in virtue of time division multiple access and are synchronized by GPS time to collect data. All monitoring data is archived and compressed in format of RINEX (Receiver Independent Exchange). The uploading data and downloading control command to and from monitoring center is transferred by Iridium communication in automatic retransmission request and broken-point continuing mechanism.

This dissertation addresses the problem of inferring scene depth information from a collection of calibrated images taken from different viewpoints via stereo matching. Although it has been heavily investigated for decades, depth from stereo remains a long-standing challenge and popular research topic for several reasons. First of all, in order to be of practical use for many real-time applications such as autonomous driving, accurate depth estimation in real-time is of great importance and one of the core challenges in stereo. Second, for applications such as 3D reconstruction and view synthesis, high-quality depth estimation is crucial to achieve photo realistic results. However, due to the matching ambiguities, accurate dense depth estimates are difficult to achieve. Last but not least, most stereo algorithms rely on identification of corresponding points among images and only work effectively when scenes are Lambertian. For non-Lambertian surfaces, the "brightness constancy" assumption is no longer valid. This dissertation contributes three novel stereo algorithms that are motivated by the specific requirements and limitations imposed by different applications. In addressing high speed depth estimation from images, we present a stereo algorithm that achieves high quality results while maintaining real-time performance. We introduce an adaptive aggregation step in a dynamic-programming framework. Matching costs are aggregated in the vertical direction using a computationally expensive weighting scheme based on color and distance proximity. We utilize the vector processing capability and parallelism in commodity graphics hardware to speed up this process over two orders of magnitude. In addressing high accuracy depth estimation, we present a stereo model that makes use of constraints from points with known depths - the Ground Control Points (GCPs) as referred to in stereo literature. Our formulation explicitly models the influences of GCPs in a Markov Random Field. A novel regularization prior is naturally integrated into a global inference framework in a principled way using the Bayes rule. Our probabilistic framework allows GCPs to be obtained from various modalities and provides a natural way to integrate information from various sensors. In addressing non-Lambertian reflectance, we introduce a new invariant for stereo correspondence which allows completely arbitrary scene reflectance (bidirectional reflectance distribution functions - BRDFs). This invariant can be used to formulate a rank constraint on stereo matching when the scene is observed by several lighting configurations in which only the lighting intensity varies.

<p>This thesis discusses how a historic woman is represented on stage today. The woman in mind is Sabina Spielrein, and she is portrayed in a play called: Name: Spielrein Sabina. She was born in the late 19th century and made a significant impact on the development in psycho-analysis. Since her letters, diaries and fragments was found 1977, and later on in 1982, nu-merous of people have been fascinated regarding her life, especially with her relation to Jung and Freud. One of my arguments is that there could be another story to tell, as she is living in a context when women were organized and struggled for their rights on many levels. It is a period when a new type of women is formulated, with new visions on society, morals and sexuality. This New Woman discourse was intense all over Europe.</p><p>With representation as a theoretical instrument it was possible to see how this play challenges several typical women images. By using the character Sabina I have looked at (stereo) types such as: the good daughter, the mad woman, the genius, the mistress, the wife and the mother. Putting Sabina Spielrein in focus has also made it possible to discuss around cultural power, how it works and the importance of who is in charge.</p>

In recent years there has been significant progress in increasing the scope, accuracy and flexibility of 3D photography methods. However there are still significant open problems where complex optical properties of mirroring or transparent objects cause many assumptions of traditional algorithms to break down. In this work we present three approaches that attempt to deal with some of these challenges using a few camera views and simple illumination. First, we consider the problem of reconstructing the 3D position and surface normal of points on a time-varying refractive surface. We show that two viewpoints are sufficient to solve this problem in the general case, even if the refractive index is unknown. We introduce a novel ``stereo matching'' criterion called refractive disparity, appropriate for refractive scenes, and develop an optimization-based algorithm for individually reconstructing the position and normal of each point projecting to a pixel in the input views. Second, we present a new method for reconstructing the exterior surface of a complex transparent scene with inhomogeneous interior. We capture images from each viewpoint while moving a proximal light source to a 2D or 3D set of positions giving a 2D (or 3D) dataset per pixel, called the scatter-trace. The key is that while light transport within a transparent scene's interior can be exceedingly complex, a pixel's scatter trace has a highly-constrained geometry that reveals the direct surface reflection, and leads to a simple ``Scatter-trace stereo'' algorithm for computing the exterior surface geometry. Finally, we develop a reconstruction system for scenes with reflectance properties ranging from diffuse to specular. We capture images of the scene as it is illuminated by a planar, spatially non-uniform light source. Then we show that if the source is translated to a parallel position away from the scene, a particular scene point integrates a magnified region of light from the plane. We observe this magnification at each pixel and show how it relates to the source-relative depth of the surface. Next we show how calibration relating the camera and source planes allows for robustness to specular objects and recovery of 3D surface points.

3D representation nowadays has attracted much more public attention than ever before. One of the most important techniques in this field is depth extraction. In this thesis, we first introduce a well-known stereo matching method using color segmentation and belief propagation, and make an implementation of this framework. The color-segmentation based stereo matching method performs well recently, since this method can keep the object boundaries accurate, which is very important to depth map. Based on the implemented framework of segmentation based stereo matching, we proposed a color segmentation based 2D-to-3D video conversion method using high quality motion information. In our proposed scheme, the original depth map is generated from motion parallax by optical flow calculation. After that we employ color segmentation and plane estimation to optimize the original depth map to get an improved depth map with sharp object boundaries. We also make some adjustments for optical flow calculation to improve its efficiency and accuracy. By using the motion vectors extracted from compressed video as initial values for optical flow calculation, the calculated motion vectors are more accurate within a shorter time compared with the same process without initial values. The experimental results shows that our proposed method indeed gives much more accurate depth maps with high quality edge information. Optical flow with initial values provides good original depth map, and color segmentation with plane estimation further improves the depth map by sharpening its boundaries.

The treatment of single ventricle anomalies is a formidable challenge for clinical teams caring for patients with congenital heart disease. Those patients fortunate to survive surgical palliation contend with lifelong physical limitations and late stage pathophysiology. A mechanical blood pump specifically designed to increase pressure in the great veins would augment flow through the lungs and provide hemodynamic stability until a donor heart is located. To support the development of such medical devices, this research characterized the fluid dynamics of mechanical assistance in the Fontan circulation by performing numerical analyses and particle image velocimetry (PIV) studies in a patient-specific in vitro model. This project investigated the performance of three pump prototype configurations. ANSYS-CFX was used to conduct the computational studies for a range of operating conditions and degrees of Fontan dysfunction. Pressure generation, blood trauma predictions, shear stresses, fluid streamlines, and velocity profiles were examined. Three-dimensional PIV studies were completed and compared to the numerical estimations. Computational findings and experimental data correlated to within literature expectations. Blood damage levels, shear stresses, and fluid residence times remained reasonable or below threshold limits. The blood pump configurations met expectations by achieving target design specifications for clinical application. The pumps enhanced the rate of hydraulic power gain in the cavopulmonary circuit, reduced inferior vena cava pressure, and minimally increased pulmonary arterial pressure. The blood pump with the twisted protective stent produced the most rapid increase in the rate of power gain and the highest pressure generation. The PIV measurements illustrated a strong dependency of the fluid dynamics on the patient-specific vessel geometry and the particular pump design. The pump having the twisted cage outperformed the other designs and had a dominating impact on the blood flow distribution in the cavopulmonary circuit. A strong rotational component in the flow was observed leaving the pumps. These results confirm that mechanical cavopulmonary assistance is a viable therapeutic option. Significant knowledge into a new class of blood pumps and how these pumps interact with a single ventricle physiology was gained, thus advancing the state-of-the-art in mechanical circulatory support and addressing a significant human health problem.