La création des vidéos panoramiques de haute qualité pour des contenus immersifs en VR est généralement faite à l'aide d'un appareil doté de plusieurs caméras couvrant une scène cible. Malheureusement, cette configuration introduit à la fois des artefacts spatiaux et temporels dus à la différence entre les centres optiques et à la synchronisation imparfaite. Les mesures de qualité d'image traditionnelles ne peuvent pas être utilisées pour évaluer la qualité de ces vidéos, en raison de leur incapacité à capturer des distorsions géométriques. Dans cette thèse, nous proposons des méthodes pour l'évaluation objective des vidéos panoramiques basées sur le flux optique et la saillance visuelle. Nous validons cette métrique avec une étude centrée sur l'homme qui combine l'annotation d'erreurs percues et l'eye-tracking.Un défi important pour mesurer la qualité des vidéos panoramiques est le manque d'une vérité-terrain. Nous avons étudié l'utilisation des vidéos originales comme référence pour le panorama de sortie. Nous notons que cette approche n'est pas directement applicable, car chaque pixel du panorama final peut avoir une à $N$ sources correspondant à $N$ vidéos d'entrée avec des régions se chevauchant. Nous montrons que ce problème peut être résolu en calculant l'écart type des déplacements de tous les pixels sources à partir du déplacement du panorama en tant que mesure de la distorsion. Cela permet de comparer la différence de mouvement entre deux images données dans les vidéos originales et le mouvement dans le panorama final. Les cartes de saillance basées sur la perception humaine sont utilisées pour pondérer la carte de distorsion pour un filtrage plus précis.Cette méthode a été validée par une étude centrée sur l'homme utilisant une expérience empirique. L'expérience visait à déterminer si les humains et la métrique d'évaluation détectaient et mesuraient les mêmes erreurs, et à explorer quelles erreurs sont les plus importantes pour les humains lorsqu'ils regardent une vidéo panoramique.Les méthodes décrites ont été testées et validées et fournissent des résultats intéressants en ce qui concerne la perception humaine pour les mesures de qualité. Ils ouvrent également la voie à de nouvelles méthodes d'optimisation de l'assemblage vidéo, guidées par ces mesures de qualité. / High quality panoramic videos for immersive VR content are commonly created using a rig with multiple cameras covering a target scene. Unfortunately, this setup introduces both spatial and temporal artifacts due to the difference in optical centers as well as the imperfect synchronization. Traditional image quality metrics cannot be used to assess the quality of such videos, due to their inability to capture geometric distortions. In this thesis, we propose methods for the objective assessment of panoramic videos based on optical flow and visual salience. We validate this metric with a human-centered study that combines human error annotation and eye-tracking.An important challenge in measuring quality for panoramic videos is the lack of ground truth. We have investigated the use of the original videos as a reference for the output panorama. We note that this approach is not directly applicable, because each pixel in the final panorama can have one to N sources corresponding to N input videos with overlapping regions. We show that this problem can be solved by calculating the standard deviation of displacements of all source pixels from the displacement of the panorama as a measure of distortion. This makes it possible to compare the difference in motion between two given frames in the original videos and motion in the final panorama. Salience maps based on human perception are used to weight the distortion map for more accurate filtering.This method was validated with a human-centered study using an empirical experiment. The experiment was designed to investigate whether humans and the evaluation metric detect and measure the same errors, and to explore which errors are more salient to humans when watching a panoramic video.The methods described have been tested and validated and they provide interesting findings regarding human-based perception for quality metrics. They also open the way to new methods for optimizing video stitching guided by those quality metrics.

<p>Mammographic screening is an effective way to detect breast cancer. Early detection of breast cancer depends to a high degree on the adequacy of the mammogram from which the diagnosis is made. Today, most of the analysis of the mammogram is performed by radiologists. Computer-aided diagnosis (CAD) systems have been proposed as an aid to increase the efficiency and effectiveness of the screening procedure by automatically indicating abnormalities in the mammograms. However, in order for a CAD system to be stable and efficient, the input images need to be adequate. Criteria for adequacy include: high resolution, low image noise and high image contrast. Additionally, the breast needs to be adequately positioned and compressed to properly visualise the entire breast and especially the glandular tissue.</p><p>This thesis addresses questions regarding the automatic determination of mammogram adequacy with the focus on breast positioning and segmentation evaluation. The goal and, thus, the major technical challenge is to develop algorithms that support fully automatic quality checks. The relevant quality criteria are discussed in Chapter 2. The aim of this discussion is to compile a comprehensive list of necessary criteria that a system for automatic assessment of mammographic adequacy must satisfy. Chapter 3 gives an overview of research performed in computer-aided analysis of mammograms. It also provides basic knowledge about image analysis involved in the research area of computerized mammography in general, and in the papers of this thesis, in particular. In contrast, Chapter 4 describes basic knowledge about segmentation evaluation, which is a highly important component in image analysis. Papers I–IV propose algorithms for measuring the quality of a mammogram according to certain criteria and addresses problems related to them. A method for automatic analysis of the shape of the pectoralis muscle is presented in Paper I. Paper II proposes a fully automatic method for extracting the breast border. A geometric assumption used by radiologists is that the nipple is located at the point on the breast border being furthest away from the pectoralis muscle. This assumption is investigated in Paper III, and a method for automatically restricting the search area is proposed. There has been an increasing need to develop an automated segmentation algorithm for extracting the glandular tissue, where the majority of breast cancer occur. In Paper IV, a novel approach for solving this problem in a robust and accurate way is proposed. Paper V discusses the challenges involved in evaluating the quality of segmentation algorithms based on ground truths provided by an expert panel. A method to relate ground truths provided by several experts to each other in order to establish levels of agreement is proposed. Furthermore, this work is used to develop an algorithm that combines an ensemble of markings into one surrogate ground truth.</p>

Mammographic screening is an effective way to detect breast cancer. Early detection of breast cancer depends to a high degree on the adequacy of the mammogram from which the diagnosis is made. Today, most of the analysis of the mammogram is performed by radiologists. Computer-aided diagnosis (CAD) systems have been proposed as an aid to increase the efficiency and effectiveness of the screening procedure by automatically indicating abnormalities in the mammograms. However, in order for a CAD system to be stable and efficient, the input images need to be adequate. Criteria for adequacy include: high resolution, low image noise and high image contrast. Additionally, the breast needs to be adequately positioned and compressed to properly visualise the entire breast and especially the glandular tissue. This thesis addresses questions regarding the automatic determination of mammogram adequacy with the focus on breast positioning and segmentation evaluation. The goal and, thus, the major technical challenge is to develop algorithms that support fully automatic quality checks. The relevant quality criteria are discussed in Chapter 2. The aim of this discussion is to compile a comprehensive list of necessary criteria that a system for automatic assessment of mammographic adequacy must satisfy. Chapter 3 gives an overview of research performed in computer-aided analysis of mammograms. It also provides basic knowledge about image analysis involved in the research area of computerized mammography in general, and in the papers of this thesis, in particular. In contrast, Chapter 4 describes basic knowledge about segmentation evaluation, which is a highly important component in image analysis. Papers I–IV propose algorithms for measuring the quality of a mammogram according to certain criteria and addresses problems related to them. A method for automatic analysis of the shape of the pectoralis muscle is presented in Paper I. Paper II proposes a fully automatic method for extracting the breast border. A geometric assumption used by radiologists is that the nipple is located at the point on the breast border being furthest away from the pectoralis muscle. This assumption is investigated in Paper III, and a method for automatically restricting the search area is proposed. There has been an increasing need to develop an automated segmentation algorithm for extracting the glandular tissue, where the majority of breast cancer occur. In Paper IV, a novel approach for solving this problem in a robust and accurate way is proposed. Paper V discusses the challenges involved in evaluating the quality of segmentation algorithms based on ground truths provided by an expert panel. A method to relate ground truths provided by several experts to each other in order to establish levels of agreement is proposed. Furthermore, this work is used to develop an algorithm that combines an ensemble of markings into one surrogate ground truth.

Biometric systems allow identification of human persons based on physiological or behavioral characteristics, such as voice, handprint, iris or facial characteristics. The use of face and iris recognition as a way to authenticate user’s identities has been a topic of research for years. Present iris recognition systems require that subjects stand close (<2m) to the imaging camera and look for a period of about three seconds until the data are captured. This cooperative behavior is required in order to capture quality images for accurate recognition. This will eventually restrict the amount of practical applications where iris recognition can be applied, especially in an uncontrolled environment where subjects are not expected to cooperate such as criminals and terrorists, for example. For this reason, this thesis develops a collection of methods to deal with low quality face and iris images and that can be applied for face and iris recognition in a non-cooperative environment. This thesis makes the following main contributions: I. For eye and face tracking in low quality images, a new robust method is developed. The proposed system consists of three parts: face localization, eye detection and eye tracking. This is accomplished using traditional image-based passive techniques such as shape information of the eye and active based methods which exploit the spectral properties of the pupil under IR illumination. The developed method is also tested on underexposed images where the subject shows large head movements. II. For iris recognition, a new technique is developed for accurate iris segmentation in low quality images where a major portion of the iris is occluded. Most existing methods perform generally quite well but tend to overestimate the occluded regions, and thus lose iris information that could be used for identification. This information loss is potentially important in the covert surveillance applications we consider in this thesis. Once the iris region is properly segmented using the developed method, the biometric feature information is calculated for the iris region using the relative entropy technique. Iris biometric feature information is calculated using two different feature decomposition algorithms based on Principal Component Analysis (PCA) and Independent Component Analysis (ICA). III. For face recognition, a new approach is developed to measure biometric feature information and the changes in biometric sample quality resulting from image degradations. A definition of biometric feature information is introduced and an algorithm to measure it proposed, based on a set of population and individual biometric features, as measured by a biometric algorithm under test. Examples of its application were shown for two different face recognition algorithms based on PCA (Eigenface) and Fisher Linear Discriminant (FLD) feature decompositions.

Mechanical manipulation and characterization of biological cells have wide applications in genetics, reproductive biology, and cell mechanics. This research focuses on (1) the development of enabling microrobotic systems and techniques for automated cell microinjection and in situ mechanical characterization; and (2) the demonstration of molecule efficacy testing and cell quality assessment with the new technologies. Targeting high-speed cell injection for molecule screening, a first-of-its-kind automated microrobotic cell injection system is developed for injecting foreign materials (e.g., DNA, morpholinos, and proteins) into zebrafish embryos (~1.2 millimeter) and mouse oocytes/embryos (~100 micrometers), which overcomes the problems inherent in manual operation, such as long learning curves, human fatigue, and large variations in success rates due to poor reproducibility. Novel cell holding devices are developed for immobilizing a large number of embryos into a regular pattern, greatly facilitating sample preparation and increasing the sample preparation speed. Leveraging motion control and computer vision techniques, the microrobotic system is capable of performing robust cell injection at a high speed with high survival, success, and phenotypic rates. The mouse embryo injection system is applied to molecule testing of recombinant mitochondrial proteins. The efficacy of an anti-apoptotic Bcl-xL (Delta_TM) protein is, for the first time, quantitatively evaluated for enhancing the development competence of mouse embryos. For cell quality assessment, this research develops a vision-based technique for real-time cellular force measurement and in situ mechanical characterization of individual cells during microinjection. A microfabricated elastic device and a sub-pixel computer vision tracking algorithm together resolve cellular forces at the nanonewton level. Experimental results on young and old mouse oocytes demonstrate that the in situ obtained force-deformation data can be used for mechanically distinguishing healthy mouse oocytes from those with cellular dysfunctions. This work represents the first study that quantified the mechanical difference between young and old mouse oocytes, promising a practical way for oocyte quality assessment during microinjection.

Mechanical manipulation and characterization of biological cells have wide applications in genetics, reproductive biology, and cell mechanics. This research focuses on (1) the development of enabling microrobotic systems and techniques for automated cell microinjection and in situ mechanical characterization; and (2) the demonstration of molecule efficacy testing and cell quality assessment with the new technologies. Targeting high-speed cell injection for molecule screening, a first-of-its-kind automated microrobotic cell injection system is developed for injecting foreign materials (e.g., DNA, morpholinos, and proteins) into zebrafish embryos (~1.2 millimeter) and mouse oocytes/embryos (~100 micrometers), which overcomes the problems inherent in manual operation, such as long learning curves, human fatigue, and large variations in success rates due to poor reproducibility. Novel cell holding devices are developed for immobilizing a large number of embryos into a regular pattern, greatly facilitating sample preparation and increasing the sample preparation speed. Leveraging motion control and computer vision techniques, the microrobotic system is capable of performing robust cell injection at a high speed with high survival, success, and phenotypic rates. The mouse embryo injection system is applied to molecule testing of recombinant mitochondrial proteins. The efficacy of an anti-apoptotic Bcl-xL (Delta_TM) protein is, for the first time, quantitatively evaluated for enhancing the development competence of mouse embryos. For cell quality assessment, this research develops a vision-based technique for real-time cellular force measurement and in situ mechanical characterization of individual cells during microinjection. A microfabricated elastic device and a sub-pixel computer vision tracking algorithm together resolve cellular forces at the nanonewton level. Experimental results on young and old mouse oocytes demonstrate that the in situ obtained force-deformation data can be used for mechanically distinguishing healthy mouse oocytes from those with cellular dysfunctions. This work represents the first study that quantified the mechanical difference between young and old mouse oocytes, promising a practical way for oocyte quality assessment during microinjection.

Biometric systems allow identification of human persons based on physiological or behavioral characteristics, such as voice, handprint, iris or facial characteristics. The use of face and iris recognition as a way to authenticate user’s identities has been a topic of research for years. Present iris recognition systems require that subjects stand close (<2m) to the imaging camera and look for a period of about three seconds until the data are captured. This cooperative behavior is required in order to capture quality images for accurate recognition. This will eventually restrict the amount of practical applications where iris recognition can be applied, especially in an uncontrolled environment where subjects are not expected to cooperate such as criminals and terrorists, for example. For this reason, this thesis develops a collection of methods to deal with low quality face and iris images and that can be applied for face and iris recognition in a non-cooperative environment. This thesis makes the following main contributions: I. For eye and face tracking in low quality images, a new robust method is developed. The proposed system consists of three parts: face localization, eye detection and eye tracking. This is accomplished using traditional image-based passive techniques such as shape information of the eye and active based methods which exploit the spectral properties of the pupil under IR illumination. The developed method is also tested on underexposed images where the subject shows large head movements. II. For iris recognition, a new technique is developed for accurate iris segmentation in low quality images where a major portion of the iris is occluded. Most existing methods perform generally quite well but tend to overestimate the occluded regions, and thus lose iris information that could be used for identification. This information loss is potentially important in the covert surveillance applications we consider in this thesis. Once the iris region is properly segmented using the developed method, the biometric feature information is calculated for the iris region using the relative entropy technique. Iris biometric feature information is calculated using two different feature decomposition algorithms based on Principal Component Analysis (PCA) and Independent Component Analysis (ICA). III. For face recognition, a new approach is developed to measure biometric feature information and the changes in biometric sample quality resulting from image degradations. A definition of biometric feature information is introduced and an algorithm to measure it proposed, based on a set of population and individual biometric features, as measured by a biometric algorithm under test. Examples of its application were shown for two different face recognition algorithms based on PCA (Eigenface) and Fisher Linear Discriminant (FLD) feature decompositions.

Three dimensional television (3DTV) is believed to be the future of television broadcasting that will replace current 2D HDTV technology. In the future, 3DTV will bring a more life-like and visually immersive home entertainment experience, in which users will have the freedom to navigate through the scene to choose a different viewpoint. A desired view can be synthesized at the receiver side using depth image-based rendering (DIBR). While this approach has many advantages, one of the key challenges in DIBR is generating high quality synthesized views. This work presents novel methods to measure and enhance the quality of 3D videos generated through DIBR. For quality measurements we describe a novel method to characterize and measure distortions by multiple cameras used to capture stereoscopic images. In addition, we present an objective quality measure for DIBR-based 3D videos by evaluating the elements of visual discomfort in stereoscopic 3D videos. We also introduce a new concept called the ideal depth estimate, and define the tools to estimate that depth. Full-reference and no-reference profiles for calculating the proposed measures are also presented. Moreover, we introduce two innovative approaches to improve the quality of the synthesized views generated by DIBR. The first approach is based on hierarchical blending of the background and foreground information around the disocclusion areas which produces a natural looking, synthesized view with seamless hole-filling. This approach yields virtual images that are free of any geometric distortions, unlike other algorithms that preprocess the depth map. In contrast to the other hole-filling approaches, our approach is not sensitive to depth maps with high percentage of bad pixels from stereo matching. The second approach further enhances the results through a depth-adaptive preprocessing of the colored images. Finally, we propose an enhancement over depth estimation algorithm using the depth monocular cues from luminance and chrominance. The estimated depth will be evaluated using our quality measure, and the hole-filling algorithm will be used to generate synthesized views. This application will demonstrate how our quality measures and enhancement algorithms could help in the development of high quality stereoscopic depth-based synthesized videos.

Magistro baigiamajame darbe išanalizuota ir įvertinta „Šv. Juozapo globos namų“ vidaus ir išorės aplinkos veiksnių kompleksinė įtaka, identifikuotos probleminės sritys ir tuo remiantis sudaromos prielaidos organizacijos strategijos formavimui bei strateginio plano rengimui. Pirmoje darbo dalyje teoriniu aspektu apibrėžiamos socialinės globos paslaugos, strateginio planavimo teoriniai aspektai ir socialinių globos paslaugų kokybės vertinimo ypatumai apžvelgiant paslaugų kokybės vertinimo modelius bei užsienio valstybių empirinius tyrimus. Antroje dalyje, remiantis tam tikrais metodais (Porter 5 jėgos, PEST, 7 - S, SSGG), atliekama „Šv. Juozapo globos namų“ strateginė analizė. Trečioje darbo dalyje pateikiama „Šv. Juozapo globos namų“ socialinės globos paslaugų kokybės empirinio tyrimo metodika bei organizavimas ir rezultatų analizė. Tyrimo tikslas - palyginti socialines paslaugas į namus gaunančių asmenų bei jų artimųjų ir globos įstaigoje gyvenančių asmenų bei jų artimųjų požiūrį į jiems teikiamų paslaugų kokybę bei identifikuoti kokybės kriterijus, darančius didžiausią įtaką bendram kokybės įvertinimui. Atsižvelgiant į strateginės analizės rezultatus pateikiami siūlymai organizacijos veiklos tobulinimui. / This Master's thesis analyzes and evaluates St. Joseph's Care Home’s internal and external environmental factors’ complex influence, identifies problematic areas and leads to the preconditions for organization's strategy formulation and preparation of strategic plan. The first part of the thesis defines the theoretical terms of social care services, strategic planning in theory and the peculiarities of social care services quality assessment by reviewing service quality evaluation models and empirical studies from foreign countries. The strategic analysis of St. Joseph's Care Home is performed in the second part of this thesis basing on certain techniques (Porter's five forces, PEST, 7 – S, SWOT). The third part of the thesis provides the methodology of St. Joseph's Care Home empirical research on social care service quality, organization and analysis of the results. The aimof the research is to compare the attitudes on services quality of individuals and their family members, who receive social services athomeand the ones living in carehome; also to identify the quality criteria that havethe greatestimpact on the general qualityassessment. Based on the results of strategic analysis the suggestions on how to improve organization’s performance are provided.

Darbe nagrinėjamas vienas iš vaizdų kokybės vertinimo metodų (metrikų) – SSIM (struktūrinio panašumo) indekso metodas bei šio metodo naudojimas tiriant didelius vaizdus. Darbo eigoje: • nustatyta kai kurių įgyvendintų SSIM indekso algoritmų problematika, vertinant aukštos raiškos vaizdus; • nustatytos gaunamų skaitinių reikšmių priklausomybės nuo tiriamų vaizdų dydžio; • pagrindžiamas vaizdo duomenų mažinimas SSIM indekso algoritmuose; • pasiūlyti tam tikri sprendimai SSIM indekso algoritmo sudarymui, skirto didelės raiškos vaizdų vertinimui; • palyginti SSIM indekso algoritmų veikimo laikai tarp skirtingų algoritmų; • sukurta programinė įranga, kuri yra pritaikyta Windows operacinei sistemai bei gali būti patogiai įdiegta kompiuteryje. Programoje: – patobulintas SSIM indekso įgyvendinimo algoritmas; – atvaizduojamas SSIM skirtumų žemėlapis; – sukurta patogi vartotojui vizualinė aplinka. Realizuota programinė įranga gali būti naudojama edukaciniais tikslais bei užsakomiesiems apdorotų vaizdų kokybės vertinimo tyrimams. / The paper analyzes one of image quality assessment methods (metrics) – SSIM (structural similarity) index method, and this method in order to analyze the large images. In work process: • problems of some SSIM index algorithms for high-resolution images have been identified; • dependence of image size and SSIM index values has been found; • some solutions for SSIM index algorithm for high-resolution images have been proposed; • the image data down sampling in SSIM index algorithms has justified; • SSIM index algorithm run times between different algorithms has been compared; • Software which is designed for MS Windows operating system and can be easily installed on the computer has been developed. In this software: – SSIM index algorithm is updated; – program Displays the SSIM index map; – User-friendly visual environment is developed. Implemented software can be used for educational purposes and commercial use for analyzing processed image quality assessment.