Lip syncing method for realistic expressive 3D face model

Lip synchronization of 3D face model is now being used in a multitude of important fields. It brings a more human, social and dramatic reality to computer games, films and interactive multimedia, and is growing in use and importance. High level of realism can be used in demanding applications such as computer games and cinema. Authoring lip syncing with complex and subtle expressions is still difficult and fraught with problems in terms of realism. This research proposed a lip syncing method of realistic expressive 3D face model. Animated lips requires a 3D face model capable of representing the myriad shapes the human face experiences during speech and a method to produce the correct lip shape at the correct time. The paper presented a 3D face model designed to support lip syncing that align with input audio file. It deforms using Raised Cosine Deformation (RCD) function that is grafted onto the input facial geometry. The face model was based on MPEG-4 Facial Animation (FA) Standard. This paper proposed a method to animate the 3D face model over time to create animated lip syncing using a canonical set of visemes for all pairwise combinations of a reduced phoneme set called ProPhone. The proposed research integrated emotions by the consideration of Ekman model and Plutchik’s wheel with emotive eye movements by implementing Emotional Eye Movements Markup Language (EEMML) to produce realistic 3D face model. © 2017 Springer Science+Business Media New Yor

Automatic Fitting of a Deformable Face Mask Using a Single Image

We propose an automatic method for person-independent fitting of a deformable 3D face mask model under varying illumination conditions. Principle Component Analysis is utilised to build a face model which is then used within a particle filter based approach to fit the mask to the image. By subdividing a coarse mask and using a novel texture mapping technique, we further apply the 3D face model to fit into lower resolution images. The illumination invariance is achieved by representing each face as a combination of harmonic images within the weighting function of the particle filter. We demonstrate the performance of our approach on the IMM Face Database and the Extended Yale Face Database and show that it out performs the Active Shape Models approach

Framework for Contextual Outlier Identification using Multivariate Analysis approach and Unsupervised Learning

Majority of the existing commercial application for video surveillance system only captures the event frames where the accuracy level of captures is too poor. We reviewed the existing system to find that at present there is no such research technique that offers contextual-based scene identification of outliers. Therefore, we presented a framework that uses unsupervised learning approach to perform precise identification of outliers for a given video frames concerning the contextual information of the scene. The proposed system uses matrix decomposition method using multivariate analysis to maintain an equilibrium better faster response time and higher accuracy of the abnormal event/object detection as an outlier. Using an analytical methodology, the proposed system blocking operation followed by sparsity to perform detection. The study outcome shows that proposed system offers an increasing level of accuracy in contrast to the existing system with faster response time

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

Efficient facial animation integrating Euclidean and geodesic distance-based algorithms into radial basis function interpolation.

Facial animation has been an important research topic during the last decades. There has been considerable effort on the efficient creation of realistic and believable facial expressions. Among various approaches for creating believable movements in human facial features, one of the most common utilises motion capture. This thesis explores the current approaches on facial animation with this technology together with Radial Basis Function (RBF) interpolation, covering a review of Euclidean and geodesic distance-based algorithms, and proposing a hybrid approach that tries to take the advantages of the two previous methods aided by pre-processed distance data to fasten the computations. Using motion capture performance based on the Facial Action Coding System (FACS), the results are then evaluated with a wide range of facial expressions in both a realistic and a stylised facial model. The findings of this thesis show the advantage of the hybrid RBF approach proposed which, combined with pre-processed distance data, results in a more efficient and more accurate process for the generation of high-detail facial animation with motion capture

Videos in Context for Telecommunication and Spatial Browsing

The research presented in this thesis explores the use of videos embedded in panoramic imagery to transmit spatial and temporal information describing remote environments and their dynamics. Virtual environments (VEs) through which users can explore remote locations are rapidly emerging as a popular medium of presence and remote collaboration. However, capturing visual representation of locations to be used in VEs is usually a tedious process that requires either manual modelling of environments or the employment of specific hardware. Capturing environment dynamics is not straightforward either, and it is usually performed through specific tracking hardware. Similarly, browsing large unstructured video-collections with available tools is difficult, as the abundance of spatial and temporal information makes them hard to comprehend. At the same time, on a spectrum between 3D VEs and 2D images, panoramas lie in between, as they offer the same 2D images accessibility while preserving 3D virtual environments surrounding representation. For this reason, panoramas are an attractive basis for videoconferencing and browsing tools as they can relate several videos temporally and spatially. This research explores methods to acquire, fuse, render and stream data coming from heterogeneous cameras, with the help of panoramic imagery. Three distinct but interrelated questions are addressed. First, the thesis considers how spatially localised video can be used to increase the spatial information transmitted during video mediated communication, and if this improves quality of communication. Second, the research asks whether videos in panoramic context can be used to convey spatial and temporal information of a remote place and the dynamics within, and if this improves users' performance in tasks that require spatio-temporal thinking. Finally, the thesis considers whether there is an impact of display type on reasoning about events within videos in panoramic context. These research questions were investigated over three experiments, covering scenarios common to computer-supported cooperative work and video browsing. To support the investigation, two distinct video+context systems were developed. The first telecommunication experiment compared our videos in context interface with fully-panoramic video and conventional webcam video conferencing in an object placement scenario. The second experiment investigated the impact of videos in panoramic context on quality of spatio-temporal thinking during localization tasks. To support the experiment, a novel interface to video-collection in panoramic context was developed and compared with common video-browsing tools. The final experimental study investigated the impact of display type on reasoning about events. The study explored three adaptations of our video-collection interface to three display types. The overall conclusion is that videos in panoramic context offer a valid solution to spatio-temporal exploration of remote locations. Our approach presents a richer visual representation in terms of space and time than standard tools, showing that providing panoramic contexts to video collections makes spatio-temporal tasks easier. To this end, videos in context are suitable alternative to more difficult, and often expensive solutions. These findings are beneficial to many applications, including teleconferencing, virtual tourism and remote assistance

Model based methods for locating, enhancing and recognising low resolution objects in video

Visual perception is our most important sense which enables us to detect and recognise objects even in low detail video scenes. While humans are able to perform such object detection and recognition tasks reliably, most computer vision algorithms struggle with wide angle surveillance videos that make automatic processing difficult due to low resolution and poor detail objects. Additional problems arise from varying pose and lighting conditions as well as non-cooperative subjects. All these constraints pose problems for automatic scene interpretation of surveillance video, including object detection, tracking and object recognition.Therefore, the aim of this thesis is to detect, enhance and recognise objects by incorporating a priori information and by using model based approaches. Motivated by the increasing demand for automatic methods for object detection, enhancement and recognition in video surveillance, different aspects of the video processing task are investigated with a focus on human faces. In particular, the challenge of fully automatic face pose and shape estimation by fitting a deformable 3D generic face model under varying pose and lighting conditions is tackled. Principal Component Analysis (PCA) is utilised to build an appearance model that is then used within a particle filter based approach to fit the 3D face mask to the image. This recovers face pose and person-specific shape information simultaneously. Experiments demonstrate the use in different resolution and under varying pose and lighting conditions. Following that, a combined tracking and super resolution approach enhances the quality of poor detail video objects. A 3D object mask is subdivided such that every mask triangle is smaller than a pixel when projected into the image and then used for model based tracking. The mask subdivision then allows for super resolution of the object by combining several video frames. This approach achieves better results than traditional super resolution methods without the use of interpolation or deblurring.Lastly, object recognition is performed in two different ways. The first recognition method is applied to characters and used for license plate recognition. A novel character model is proposed to create different appearances which are then matched with the image of unknown characters for recognition. This allows for simultaneous character segmentation and recognition and high recognition rates are achieved for low resolution characters down to only five pixels in size. While this approach is only feasible for objects with a limited number of different appearances, like characters, the second recognition method is applicable to any object, including human faces. Therefore, a generic 3D face model is automatically fitted to an image of a human face and recognition is performed on a mask level rather than image level. This approach does not require an initial pose estimation nor the selection of feature points, the face alignment is provided implicitly by the mask fitting process