Speech-driven Animation with Meaningful Behaviors

Conversational agents (CAs) play an important role in human computer interaction. Creating believable movements for CAs is challenging, since the movements have to be meaningful and natural, reflecting the coupling between gestures and speech. Studies in the past have mainly relied on rule-based or data-driven approaches. Rule-based methods focus on creating meaningful behaviors conveying the underlying message, but the gestures cannot be easily synchronized with speech. Data-driven approaches, especially speech-driven models, can capture the relationship between speech and gestures. However, they create behaviors disregarding the meaning of the message. This study proposes to bridge the gap between these two approaches overcoming their limitations. The approach builds a dynamic Bayesian network (DBN), where a discrete variable is added to constrain the behaviors on the underlying constraint. The study implements and evaluates the approach with two constraints: discourse functions and prototypical behaviors. By constraining on the discourse functions (e.g., questions), the model learns the characteristic behaviors associated with a given discourse class learning the rules from the data. By constraining on prototypical behaviors (e.g., head nods), the approach can be embedded in a rule-based system as a behavior realizer creating trajectories that are timely synchronized with speech. The study proposes a DBN structure and a training approach that (1) models the cause-effect relationship between the constraint and the gestures, (2) initializes the state configuration models increasing the range of the generated behaviors, and (3) captures the differences in the behaviors across constraints by enforcing sparse transitions between shared and exclusive states per constraint. Objective and subjective evaluations demonstrate the benefits of the proposed approach over an unconstrained model.Comment: 13 pages, 12 figures, 5 table

A framework for automatic and perceptually valid facial expression generation

Facial expressions are facial movements reflecting the internal emotional states of a character or in response to social communications. Realistic facial animation should consider at least two factors: believable visual effect and valid facial movements. However, most research tends to separate these two issues. In this paper, we present a framework for generating 3D facial expressions considering both the visual the dynamics effect. A facial expression mapping approach based on local geometry encoding is proposed, which encodes deformation in the 1-ring vector. This method is capable of mapping subtle facial movements without considering those shape and topological constraints. Facial expression mapping is achieved through three steps: correspondence establishment, deviation transfer and movement mapping. Deviation is transferred to the conformal face space through minimizing the error function. This function is formed by the source neutral and the deformed face model related by those transformation matrices in 1-ring neighborhood. The transformation matrix in 1-ring neighborhood is independent of the face shape and the mesh topology. After the facial expression mapping, dynamic parameters are then integrated with facial expressions for generating valid facial expressions. The dynamic parameters were generated based on psychophysical methods. The efficiency and effectiveness of the proposed methods have been tested using various face models with different shapes and topological representations

A Survey of Multimedia Technologies and Robust Algorithms

Multimedia technologies are now more practical and deployable in real life, and the algorithms are widely used in various researching areas such as deep learning, signal processing, haptics, computer vision, robotics, and medical multimedia processing. This survey provides an overview of multimedia technologies and robust algorithms in multimedia data processing, medical multimedia processing, human facial expression tracking and pose recognition, and multimedia in education and training. This survey will also analyze and propose a future research direction based on the overview of current robust algorithms and multimedia technologies. We want to thank the research and previous work done by the Multimedia Research Centre (MRC), the University of Alberta, which is the inspiration and starting point for future research.Comment: arXiv admin note: text overlap with arXiv:2010.1296

Spatio-temporal centroid based sign language facial expressions for animation synthesis in virtual environment

Orientador: Eduardo TodtTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa : Curitiba, 20/02/2019Inclui referências: p.86-97Área de concentração: Ciência da ComputaçãoResumo: Formalmente reconhecida como segunda lingua oficial brasileira, a BSL, ou Libras, conta hoje com muitas aplicacoes computacionais que integram a comunidade surda nas atividades cotidianas, oferecendo interpretes virtuais representados por avatares 3D construidos utilizando modelos formais que parametrizam as caracteristicas especificas das linguas de sinais. Estas aplicacoes, contudo, ainda consideram expressoes faciais como recurso de segundo plano em uma lingua primariamente gestual, ignorando a importancia que expressoes faciais e emocoes imprimem no contexto da mensagem transmitida. Neste trabalho, a fim de definir um modelo facial parametrizado para uso em linguas de sinais, um sistema de sintese de expressoes faciais atraves de um avatar 3D e proposto e um prototipo implementado. Neste sentido, um modelo de landmarks faciais separado por regioes e definido assim como uma modelagem de expressoes base utilizando as bases faciais AKDEF e JAFEE como referencia. Com este sistema e possivel representar expressoes complexas utilizando interpolacao dos valores de intensidade na animacao geometrica, de forma simplificada utilizando controle por centroides e deslocamento de regioes independentes no modelo 3D. E proposto ainda uma aplicacao de modelo espaco-temporal para os landmarks faciais, com o objetivo de observar o comportamento e relacao dos centroides na sintese das expressoes base definindo quais pontos geometricos sao relevantes no processo de interpolacao e animacao das expressoes. Um sistema de exportacao dos dados faciais seguindo o formato hierarquico utilizado na maioria dos avatares 3D interpretes de linguas de sinais e desenvolvido, incentivando a integracao em modelos formais computacionais ja existentes na literatura, permitindo ainda a adaptacao e alteracao de valores e intensidades na representacao das emocoes. Assim, os modelos e conceitos apresentados propoe a integracao de um modeo facial para representacao de expressoes na sintese de sinais oferecendo uma proposta simplificada e otimizada para aplicacao dos recursos em avatares 3D. Palavras-chave: Avatar 3D, Dados Espaco-Temporal, Libras, Lingua de sinais, Expressoes Faciais.Abstract: Formally recognized as the second official Brazilian language, BSL, or Libras, today has many computational applications that integrate the deaf community into daily activities, offering virtual interpreters represented by 3D avatars built using formal models that parameterize the specific characteristics of sign languages. These applications, however, still consider facial expressions as a background feature in a primarily gestural language, ignoring the importance that facial expressions and emotions imprint on the context of the transmitted message. In this work, in order to define a parametrized facial model for use in sign languages, a system of synthesis of facial expressions through a 3D avatar is proposed and a prototype implemented. In this way, a model of facial landmarks separated by regions is defined as a modeling of base expressions using the AKDEF and JAFEE facial bases as a reference. With this system it is possible to represent complex expressions using interpolation of the intensity values in the geometric animation, in a simplified way using control by centroids and displacement of independent regions in the 3D model. A spatial-temporal model is proposed for the facial landmarks, with the objective of define the behavior and relation of the centroids in the synthesis of the basic expressions, pointing out which geometric landmark are relevant in the process of interpolation and animation of the expressions. A system for exporting facial data following the hierarchical format used in most avatars 3D sign language interpreters is developed, encouraging the integration in formal computer models already existent in the literature, also allowing the adaptation and change of values and intensities in the representation of the emotions. Thus, the models and concepts presented propose the integration of a facial model to represent expressions in the synthesis of signals offering a simplified and optimized proposal for the application of the resources in 3D avatars. Keywords: 3D Avatar, Spatio-Temporal Data, BSL, Sign Language, Facial Expression

Towards sociable virtual humans : multimodal recognition of human input and behavior

One of the biggest obstacles for constructing effective sociable virtual humans lies in the failure of machines to recognize the desires, feelings and intentions of the human user. Virtual humans lack the ability to fully understand and decode the communication signals human users emit when communicating with each other. This article describes our research in overcoming this problem by developing senses for the virtual humans which enables them to hear and understand human speech, localize the human user in front of the display system, recognize hand postures and to recognize the emotional state of the human user by classifying facial expression. We report on the methods needed to perform these tasks in real-time and conclude with an outlook on promising research issues of the future

Highly automated method for facial expression synthesis

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The synthesis of realistic facial expressions has been an unexplored area for computer graphics scientists. Over the last three decades, several different construction methods have been formulated in order to obtain natural graphic results. Despite these advancements, though, current techniques still require costly resources, heavy user intervention and specific training and outcomes are still not completely realistic. This thesis, therefore, aims to achieve an automated synthesis that will produce realistic facial expressions at a low cost. This thesis, proposes a highly automated approach for achieving a realistic facial expression synthesis, which allows for enhanced performance in speed (3 minutes processing time maximum) and quality with a minimum of user intervention. It will also demonstrate a highly technical and automated method of facial feature detection, by allowing users to obtain their desired facial expression synthesis with minimal physical input. Moreover, it will describe a novel approach to the normalization of the illumination settings values between source and target images, thereby allowing the algorithm to work accurately, even in different lighting conditions. Finally, we will present the results obtained from the proposed techniques, together with our conclusions, at the end of the paper

Example Based Caricature Synthesis

The likeness of a caricature to the original face image is an essential and often overlooked part of caricature production. In this paper we present an example based caricature synthesis technique, consisting of shape exaggeration, relationship exaggeration, and optimization for likeness. Rather than relying on a large training set of caricature face pairs, our shape exaggeration step is based on only one or a small number of examples of facial features. The relationship exaggeration step introduces two definitions which facilitate global facial feature synthesis. The first is the T-Shape rule, which describes the relative relationship between the facial elements in an intuitive manner. The second is the so called proportions, which characterizes the facial features in a proportion form. Finally we introduce a similarity metric as the likeness metric based on the Modified Hausdorff Distance (MHD) which allows us to optimize the configuration of facial elements, maximizing likeness while satisfying a number of constraints. The effectiveness of our algorithm is demonstrated with experimental results