57,403 research outputs found

    Perceptual Quality-of-Experience of Stereoscopic 3D Images and Videos

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    With the fast development of 3D acquisition, communication, processing and display technologies, automatic quality assessment of 3D images and videos has become ever important. Nevertheless, recent progress on 3D image quality assessment (IQA) and video quality assessment (VQA) remains limited. The purpose of this research is to investigate various aspects of human visual quality-of-experience (QoE) when viewing stereoscopic 3D images/videos and to develop objective quality assessment models that automatically predict visual QoE of 3D images/videos. Firstly, we create a new subjective 3D-IQA database that has two features that are lacking in the literature, i.e., the inclusion of both 2D and 3D images, and the inclusion of mixed distortion types. We observe strong distortion type dependent bias when using the direct average of 2D image quality to predict 3D image quality. We propose a binocular rivalry inspired multi-scale model to predict the quality of stereoscopic images and the results show that the proposed model eliminates the prediction bias, leading to significantly improved quality predictions. Second, we carry out two subjective studies on depth perception of stereoscopic 3D images. The first one follows a traditional framework where subjects are asked to rate depth quality directly on distorted stereopairs. The second one uses a novel approach, where the stimuli are synthesized independent of the background image content and the subjects are asked to identify depth changes and label the polarities of depth. Our analysis shows that the second approach is much more effective at singling out the contributions of stereo cues in depth perception. We initialize the notion of depth perception difficulty index (DPDI) and propose a novel computational model for DPDI prediction. The results show that the proposed model leads to highly promising DPDI prediction performance. Thirdly, we carry out subjective 3D-VQA experiments on two databases that contain various asymmetrically compressed stereoscopic 3D videos. We then compare different mixed-distortions asymmetric stereoscopic video coding schemes with symmetric coding methods and verify their potential coding gains. We propose a model to account for the prediction bias from using direct averaging of 2D video quality to predict 3D video quality. The results show that the proposed model leads to significantly improved quality predictions and can help us predict the coding gain of mixed-distortions asymmetric video compression. Fourthly, we investigate the problem of objective quality assessment of Multi-view-plus-depth (MVD) images, with a main focus on the pre- depth-image-based-rendering (pre-DIBR) case. We find that existing IQA methods are difficult to be employed as a guiding criterion in the optimization of MVD video coding and transmission systems when applied post-DIBR. We propose a novel pre-DIBR method based on information content weighting of both texture and depth images, which demonstrates competitive performance against state-of-the-art IQA models applied post-DIBR

    Zur Qualitätsbeurteilung von 3D-Videoobjekten

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    This thesis is focussed on the quality assessment of natural three-dimensional video objects. This novel kind of media objects allows watching a natural object (e. g. an actor) from different viewpoints, ideally from every arbitrary viewpoint. The quality assessment of such objects raises several questions to be solved. Many customary methods are not suitable for this new purpose. Firstly, several methods for the subjective and objective quality assessment of conventional video are investigated and systematized. Moreover, the manifold methods of generating 3D video objects are analysed. They cover a wide range from image-based to model-based methods. This analysis makes it possible to define the term 3D video object and to develop a model of its process. This model is applicable to all kinds of 3D video objects. In order to assess the quality of a 3D video object the definition of a reference is necessary. A 3D video object showing a sufficient quality has to to serve as reference for the 3D video object in evaluation. Furthermore, specific quality aspects of 3D video objects are pointed out, e. g., occlusions, distortions along epipolar lines, artifacts caused by compression, and a differing angle of view. Several methods like hierarchical block matching and a one-dimensional DFT are used to create mathematical models describing these quality features. There are significant restrictions for these methods. Naturally, a 3D video object can not be compared with its reference pixel by pixel. The models describing the quality features cover dynamic properties, too. They are depending on time as well as on the changing of the viewpoint. A set of quality parameters is developed using these mathematical feature models. These quality parameters consider the visual perception of the quality aspects and impairments. A methodology creating a 3D video quality metric 3DVQM based on these quality parameters is introduced. The parameter weights are determined by a successive approximation using extended subjective quality judgements. Finally, the proposed methodology is carried out exemplary by assessing a set of test objects. With this, the prediction of the subjective assessment based on the proposed objective method is evaluated.Die vorliegende Dissertation beschäftigt sich mit der Qualitätsbewertung von natürlichen dreidimensionalen Videoobjekten. Dieser neuartige Medienobjekttyp erlaubt die Betrachtung von natürlichen Objekten (z. B. einer Person) aus verschiedenen Perspektiven, die im Idealfall frei wählbar sind. Zunächst werden in dieser Arbeit die Verfahren zur objektiven und subjektiven Qualitätsbewertung von konventionellem Bewegtbild untersucht und systematisiert. Ebenso werden die vielfältigen Verfahren zur Generierung von 3D-Videoobjekten analysiert. Diese bilden ein großes Spektrum von bild- bis hin zu modellbasierten Verfahren. Auf der Grundlage dieser Analyse erfolgt eine Begriffsbestimmung und die Beschreibung eines Modells der 3D-Videoobjektgenerierung, welches für sämtliche Generierungsverfahren gültig ist. Um die Qualität von 3D-Videoobjekten zu untersuchen, wird zunächst die Referenzfrage gelöst. Als Referenzen für zu bewertende 3D-Videoobjekte dienen ausreichend gute 3D-Videoobjekte, welche denselben Inhalt darstellen. Im Weiteren werden die speziellen Qualitätsaspekte von 3D-Videoobjekten aufgezeigt, u. a. Größenfehler, Okklusionen, Epipolarverzerrungen, Kompressionsartefakte und Blickwinkelfehler. Verschiedene Verfahren wie beispielsweise das hierarchische Block-Matching und die eindimensionale DFT dienen dazu, diese Merkmale mittels mathematischer Modelle zu beschreiben. Die wichtigste Einschränkung bei der Auswahl und der Anwendung dieser Methoden ist es, dass a priori kein Bildpunktbezug vorausgesetzt werden kann. Die Merkmalsmodelle umfassen auch die dynamischen Eigenschaften, welche sowohl zeit- als auch blickpunktsänderungsabhängig sein können. Im Anschluss wird die Entwicklung von 3D-Videoobjektqualitätsmerkmalen auf Basis der mathematischen Merkmalsmodelle beschrieben. Diese Qualitätsparameter stellen einen Bezug zur visuellen Wahrnehmung der Qualitätsaspekte und Störungen dar. Es wird eine Methodik zur Bildung eines 3D-Videoobjektqualitätsmaßes 3DVQM auf Basis dieser Qualitätsparameter vorgestellt. Die Bestimmung der Gewichtungskoeffizienten erfolgt sukzessive mit Hilfe erweiterter subjektiver Bewertungsverfahren. Zum Schluss wird die vorgeschlagene Methodik exemplarisch für eine Testreihe durchgeführt. In der Auswertung werden die Möglichkeiten der objektiven Bewertung zur Prädiktion der subjektiven Qualitätsbewertung dargelegt
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