A multilinear tongue model derived from speech related MRI data of the human vocal tract

We present a multilinear statistical model of the human tongue that captures anatomical and tongue pose related shape variations separately. The model is derived from 3D magnetic resonance imaging data of 11 speakers sustaining speech related vocal tract configurations. The extraction is performed by using a minimally supervised method that uses as basis an image segmentation approach and a template fitting technique. Furthermore, it uses image denoising to deal with possibly corrupt data, palate surface information reconstruction to handle palatal tongue contacts, and a bootstrap strategy to refine the obtained shapes. Our evaluation concludes that limiting the degrees of freedom for the anatomical and speech related variations to 5 and 4, respectively, produces a model that can reliably register unknown data while avoiding overfitting effects. Furthermore, we show that it can be used to generate a plausible tongue animation by tracking sparse motion capture data

Registration and statistical analysis of the tongue shape during speech production

This thesis analyzes the human tongue shape during speech production. First, a semi-supervised approach is derived for estimating the tongue shape from volumetric magnetic resonance imaging data of the human vocal tract. Results of this extraction are used to derive parametric tongue models. Next, a framework is presented for registering sparse motion capture data of the tongue by means of such a model. This method allows to generate full three-dimensional animations of the tongue. Finally, a multimodal and statistical text-to-speech system is developed that is able to synthesize audio and synchronized tongue motion from text.Diese Dissertation beschäftigt sich mit der Analyse der menschlichen Zungenform während der Sprachproduktion. Zunächst wird ein semi-überwachtes Verfahren vorgestellt, mit dessen Hilfe sich Zungenformen von volumetrischen Magnetresonanztomographie- Aufnahmen des menschlichen Vokaltrakts schätzen lassen. Die Ergebnisse dieses Extraktionsverfahrens werden genutzt, um ein parametrisches Zungenmodell zu konstruieren. Danach wird eine Methode hergeleitet, die ein solches Modell nutzt, um spärliche Bewegungsaufnahmen der Zunge zu registrieren. Dieser Ansatz erlaubt es, dreidimensionale Animationen der Zunge zu erstellen. Zuletzt wird ein multimodales und statistisches Text-to-Speech-System entwickelt, das in der Lage ist, Audio und die dazu synchrone Zungenbewegung zu synthetisieren.German Research Foundatio

GIF: Generative Interpretable Faces

Photo-realistic visualization and animation of expressive human faces have been a long standing challenge. 3D face modeling methods provide parametric control but generates unrealistic images, on the other hand, generative 2D models like GANs (Generative Adversarial Networks) output photo-realistic face images, but lack explicit control. Recent methods gain partial control, either by attempting to disentangle different factors in an unsupervised manner, or by adding control post hoc to a pre-trained model. Unconditional GANs, however, may entangle factors that are hard to undo later. We condition our generative model on pre-defined control parameters to encourage disentanglement in the generation process. Specifically, we condition StyleGAN2 on FLAME, a generative 3D face model. While conditioning on FLAME parameters yields unsatisfactory results, we find that conditioning on rendered FLAME geometry and photometric details works well. This gives us a generative 2D face model named GIF (Generative Interpretable Faces) that offers FLAME's parametric control. Here, interpretable refers to the semantic meaning of different parameters. Given FLAME parameters for shape, pose, expressions, parameters for appearance, lighting, and an additional style vector, GIF outputs photo-realistic face images. We perform an AMT based perceptual study to quantitatively and qualitatively evaluate how well GIF follows its conditioning. The code, data, and trained model are publicly available for research purposes at http://gif.is.tue.mpg.de.Comment: International Conference on 3D Vision (3DV) 202

{3D} Morphable Face Models -- Past, Present and Future

In this paper, we provide a detailed survey of 3D Morphable Face Models over the 20 years since they were first proposed. The challenges in building and applying these models, namely capture, modeling, image formation, and image analysis, are still active research topics, and we review the state-of-the-art in each of these areas. We also look ahead, identifying unsolved challenges, proposing directions for future research and highlighting the broad range of current and future applications

Faces and hands : modeling and animating anatomical and photorealistic models with regard to the communicative competence of virtual humans

In order to be believable, virtual human characters must be able to communicate in a human-like fashion realistically. This dissertation contributes to improving and automating several aspects of virtual conversations. We have proposed techniques to add non-verbal speech-related facial expressions to audiovisual speech, such as head nods for of emphasis. During conversation, humans experience shades of emotions much more frequently than the strong Ekmanian basic emotions. This prompted us to develop a method that interpolates between facial expressions of emotions to create new ones based on an emotion model. In the area of facial modeling, we have presented a system to generate plausible 3D face models from vague mental images. It makes use of a morphable model of faces and exploits correlations among facial features. The hands also play a major role in human communication. Since the basis for every realistic animation of gestures must be a convincing model of the hand, we devised a physics-based anatomical hand model, where a hybrid muscle model drives the animations. The model was used to visualize complex hand movement captured using multi-exposure photography.Um überzeugend zu wirken, müssen virtuelle Figuren auf dieselbe Art wie lebende Menschen kommunizieren können. Diese Dissertation hat das Ziel, verschiedene Aspekte virtueller Unterhaltungen zu verbessern und zu automatisieren. Wir führten eine Technik ein, die es erlaubt, audiovisuelle Sprache durch nichtverbale sprachbezogene Gesichtsausdrücke zu bereichern, wie z.B. Kopfnicken zur Betonung. Während einer Unterhaltung empfinden Menschen weitaus öfter Emotionsnuancen als die ausgeprägten Ekmanschen Basisemotionen. Dies bewog uns, eine Methode zu entwickeln, die Gesichtsausdrücke für neue Emotionen erzeugt, indem sie, ausgehend von einem Emotionsmodell, zwischen bereits bekannten Gesichtsausdrücken interpoliert. Auf dem Gebiet der Gesichtsmodellierung stellten wir ein System vor, um plausible 3D-Gesichtsmodelle aus vagen geistigen Bildern zu erzeugen. Dieses System basiert auf einem Morphable Model von Gesichtern und nutzt Korrelationen zwischen Gesichtszügen aus. Auch die Hände spielen ein große Rolle in der menschlichen Kommunikation. Da der Ausgangspunkt für jede realistische Animation von Gestik ein überzeugendes Handmodell sein muß, entwikkelten wir ein physikbasiertes anatomisches Handmodell, bei dem ein hybrides Muskelmodell die Animationen antreibt. Das Modell wurde verwendet, um komplexe Handbewegungen zu visualisieren, die aus mehrfach belichteten Photographien extrahiert worden waren

High-quality face capture, animation and editing from monocular video

Digitization of virtual faces in movies requires complex capture setups and extensive manual work to produce superb animations and video-realistic editing. This thesis pushes the boundaries of the digitization pipeline by proposing automatic algorithms for high-quality 3D face capture and animation, as well as photo-realistic face editing. These algorithms reconstruct and modify faces in 2D videos recorded in uncontrolled scenarios and illumination. In particular, advances in three main areas offer solutions for the lack of depth and overall uncertainty in video recordings. First, contributions in capture include model-based reconstruction of detailed, dynamic 3D geometry that exploits optical and shading cues, multilayer parametric reconstruction of accurate 3D models in unconstrained setups based on inverse rendering, and regression-based 3D lip shape enhancement from high-quality data. Second, advances in animation are video-based face reenactment based on robust appearance metrics and temporal clustering, performance-driven retargeting of detailed facial models in sync with audio, and the automatic creation of personalized controllable 3D rigs. Finally, advances in plausible photo-realistic editing are dense face albedo capture and mouth interior synthesis using image warping and 3D teeth proxies. High-quality results attained on challenging application scenarios confirm the contributions and show great potential for the automatic creation of photo-realistic 3D faces.Die Digitalisierung von Gesichtern zum Einsatz in der Filmindustrie erfordert komplizierte Aufnahmevorrichtungen und die manuelle Nachbearbeitung von Rekonstruktionen, um perfekte Animationen und realistische Videobearbeitung zu erzielen. Diese Dissertation erweitert vorhandene Digitalisierungsverfahren durch die Erforschung von automatischen Verfahren zur qualitativ hochwertigen 3D Rekonstruktion, Animation und Modifikation von Gesichtern. Diese Algorithmen erlauben es, Gesichter in 2D Videos, die unter allgemeinen Bedingungen und unbekannten Beleuchtungsverhältnissen aufgenommen wurden, zu rekonstruieren und zu modifizieren. Vor allem Fortschritte in den folgenden drei Hauptbereichen tragen zur Kompensation von fehlender Tiefeninformation und der allgemeinen Mehrdeutigkeit von 2D Videoaufnahmen bei. Erstens, Beiträge zur modellbasierten Rekonstruktion von detaillierter und dynamischer 3D Geometrie durch optische Merkmale und die Shading-Eigenschaften des Gesichts, mehrschichtige parametrische Rekonstruktion von exakten 3D Modellen mittels inversen Renderings in allgemeinen Szenen und regressionsbasierter 3D Lippenformverfeinerung mittels qualitativ hochwertigen Daten. Zweitens, Fortschritte im Bereich der Computeranimation durch videobasierte Gesichtsausdrucksübertragung und temporaler Clusterbildung, Übertragung von detaillierten Gesichtsmodellen, deren Mundbewegung mit Ton synchronisiert ist, und die automatische Erstellung von personalisierten "3D Face Rigs". Schließlich werden Fortschritte im Bereich der realistischen Videobearbeitung vorgestellt, welche auf der dichten Rekonstruktion von Hautreflektionseigenschaften und der Mundinnenraumsynthese mittels bildbasierten und geometriebasierten Verfahren aufbauen. Qualitativ hochwertige Ergebnisse in anspruchsvollen Anwendungen untermauern die Wichtigkeit der geleisteten Beiträgen und zeigen das große Potential der automatischen Erstellung von realistischen digitalen 3D Gesichtern auf

Evolution Science and Imago Dei: A Richer and More Robust Treatment of Theological Anthropology

In my thesis, Evolution Science and the Imago Dei: A Richer and more Robust Treatment of Theological Anthropology, the first chapter demonstrates, from the historical analysis of the content attributed to the concept imago Dei over the centuries, that different ages in the Church have interpreted the content of that expression in different ways. From this historical analysis that the imago Dei assumes different meanings at different points in history, I justify my expectation that the term is open to ever new meanings. With the second chapter, by exploring the evolutionary contribution to the emergence of modern human, I establish the similarity and divergence between humans and nonhumans, genetically and phenotypically. In the third chapter, I criticize the exclusive reference of the imago Dei to only humans. Even though humans continue to be special and distinct from other species, human species has a lot in common with nonhuman species. Evolutionary science helps demonstrate that what our ancestors in faith thought was unique to humans is not so. My claim is that every living species is imago Dei in different ways. Every time that there is similarity between species, there is imago Dei, and every time that there is divergence, there is imago Dei in a different way. The divergence is not a difference between members of the same species, or else there would be in the same species so many imago Dei in different ways. Rather, the divergence is the speciation, that is, the difference between species. Because we are all imago Dei, we have a purpose which is not only individual, self-centered, or universal but which is divine; therefore, the meaning of our life does not end in this life but is opened to eschatology. Because we are imago Dei, we are called to be in solidarity and to live in sincerity with each other. Solidarity, rather than having anything to do with pity or charity, affirms that as imago Dei, we all have value in the eyes of our God