Skin deformation and animation of character models based on static and dynamic ordinary differential equations.

Animated characters play an important role in the field of computer animation, simulation and games. The basic criterion of good character animation is that the animated characters should appear realistic. This can be achieve through proper skin deformations for characters. Although various skin deformation approaches (Joint-based, Example-based, Physics-based, Curve-based and PDE-based) have been developed, the problem of generating realistic skin deformations efficiently with a small data set is a big challenge. In order to address the limitations of skin deformation, this thesis presents a workflow consisting of three main steps. First, the research has developed a new statistical method to determine the positions of joints based on available X-ray images. Second, an effective method for transferring the deformations of the curves to the polygonal model with high accuracy has been developed. Lastly, the research has produced a simple and efficient method to animate skin deformations by introducing a curved-based surface manipulation method combined with physics and data-driven approaches. The novelty of this method depends on a new model of dynamic deformations and an efficient finite difference solution of the model. The application examples indicate that the curve-based dynamic method developed in this thesis can achieve good realism and high computational efficiency with small data sets in the creation of skin deformations

Characteristics of Pro-c Analogies and Blends between Research Publications

Dr Inventor is a tool that aims to enhance the professional (Pro-c) creativity of researchers by suggesting novel hypotheses, arising from analogies between publications. Dr Inventor processes original research documents using a combination of lexical analysis and cognitive computation to identify novel comparisons that suggest new research hypotheses, with the objective of supporting a novel research publication. Research on analogical reasoning strongly suggests that the value of analogy-based comparisons depends primarily on the strength of the mapping (or counterpart projection) between the two analogs. An evaluation study of a number of computer generated comparisons attracted creativity ratings from a group of practising researchers. This paper explores a variety of theoretically motivated metrics operating on different conceptual spaces, identifying some weak associations with user's creativity ratings. Surprisingly, our results show that metrics focused on the mapping appear to have less relevance to creativity than metrics assessing the inferences (blended space). This paper includes a brief description of a research project currently exploring the best research hypothesis generated during this evaluation. Finally, we explore PCA as a means of specifying a combined multiple metrics from several blending spaces as a basis for detecting comparisons to enhance researchers’ creativity

State-of-the-Art in 3D Face Reconstruction from a Single RGB Image

Since diverse and complex emotions need to be expressed by different facial deformation and appearances, facial animation has become a serious and on-going challenge for computer animation industry. Face reconstruction techniques based on 3D morphable face model and deep learning provide one effective solution to reuse existing databases and create believable animation of new characters from images or videos in seconds, which greatly reduce heavy manual operations and a lot of time. In this paper, we review the databases and state-of-the-art methods of 3D face reconstruction from a single RGB image. First, we classify 3D reconstruction methods into three categories and review each of them. These three categories are: Shape-from-Shading (SFS), 3D Morphable Face Model (3DMM), and Deep Learning (DL) based 3D face reconstruction. Next, we introduce existing 2D and 3D facial databases. After that, we review 10 methods of deep learning-based 3D face reconstruction and evaluate four representative ones among them. Finally, we draw conclusions of this paper and discuss future research directions

Efficient and Realistic Character Animation through Analytical Physics-based Skin Deformation

Physics-based skin deformation methods can greatly improve the realism of character animation, but require non-trivial training, intensive manual intervention, and heavy numerical calculations. Due to these limitations, it is generally time-consuming to implement them, and difficult to achieve a high runtime efficiency. In order to tackle the above limitations caused by numerical calculations of physics-based skin deformation, we propose a simple and efficient analytical approach for physicsbased skin deformations. Specifically, we (1) employ Fourier series to convert 3D mesh models into continuous parametric representations through a conversion algorithm, which largely reduces data size and computing time but still keeps high realism, (2) introduce a partial differential equation (PDE)-based skin deformation model and successfully obtain the first analytical solution to physics-based skin deformations which overcomes the limitations of numerical calculations. Our approach is easy to use, highly efficient, and capable to create physically realistic skin deformations

Modelling and Simulation of Lily flowers using PDE Surfaces

This paper presents a partial differential equation (PDE)-based surface modelling and simulation framework for lily flowers. We use a PDE-based surface modelling technique to represent shape of a lily flower and PDE-based dynamic simulation to animate blossom and decay processes of lily flowers. To this aim, we first automatically construct the geometry of lily flowers from photos to obtain feature curves. Second, we apply a PDE-based surface modelling technique to generate sweeping surfaces to obtain geometric models of the flowers. Then, we use a physics-driven and data-based method and introduce the flower shapes at the initial and final positions into our proposed dynamic deformation model to generate a realistic deformation of flower blossom and decay. The results demonstrate that our proposed technique can create realistic flower models and their movements and shape changes against time efficiently with a small data size

Improving Realism of Facial Interpolation and Blendshapes with Analytical Partial Differential Equation-Represented Physics

How to create realistic shapes by interpolating two known shapes for facial blendshapes has not been investigated in the existing literature. In this paper, we propose a physics-based mathematical model and its analytical solutions to obtain more realistic facial shape changes. To this end, we first introduce the internal force of elastic beam bending into the equation of motion and integrate it with the constraints of two known shapes to develop the physics-based mathematical model represented with dynamic partial differential equations (PDEs). Second, we propose a unified mathematical expression of the external force represented with linear and various nonlinear time-dependent Fourier series, introduce it into the mathematical model to create linear and various nonlinear dynamic deformations of the curves defining a human face model, and derive analytical solutions of the mathematical model. Third, we evaluate the realism of the obtained analytical solutions in interpolating two known shapes to create new shape changes by comparing the shape changes calculated with the obtained analytical solutions and geometric linear interpolation to the ground-truth shape changes and conclude that among linear and various nonlinear PDE-based analytical solutions named as linear, quadratic, and cubic PDE-based interpolation, quadratic PDE-based interpolation creates the most realistic shape changes, which are more realistic than those obtained with the geometric linear interpolation. Finally, we use the quadratic PDE-based interpolation to develop a facial blendshape method and demonstrate that the proposed approach is more efficient than numerical physics-based facial blendshapes

Dr. Inventor, Promoting Scientific Creativity by Utilising Web-based Research Objects, FP7

Scientific creativity and innovation represent the beating heart of European growth at a time of rapid technological change. Dr Inventor is built on the vision that technologies have great potential to supplement human ingenuity in science by overcoming the limitations that people suffer in pursuing scientific discovery. It presents an original system that will provide inspiration for scientific creativity by utilising the rich presence of web-based research resources. Dr Inventor will act as a personal research assistant, utilising machine-empowered search and computation to bring researchers extended perspectives for scientific innovation by informing them of a broad spectrum of relevant research concepts and approaches, by assessing the novelty of research ideas, and by offering suggestions of new concepts and workflows with unexpected features for new scientific discovery. Dr Inventor is an attempt to understand the potential of technology in the scientific creative process within current technology limitations. It represents a sound balance between scientific insight into individual scientific creative processes and technical implementation using innovative technologies in information extraction, document summarization, semantics and visual analytics. The outcomes will be integrated into a web-based system that will allow evaluation in a selected research area under real-world settings with carefully designed metrics, benchmarks and baseline for creative performance, leading to tangible measurements on the performance of the technologies in enhancing human creativity and a blueprint for future technologies in computational creativity. Dr Inventor has huge implications for scientific innovation in Europe, as it has the potential to change the way in which scientific research is undertaken. The acceptance of the system by general research communities will open opportunities for many industrial sectors, leading to reinforced leadership of European industry

Semantic modeling of indoor scenes with support inference from a single photograph

We present an automatic approach for the semantic modeling of indoor scenes based on a single photograph, instead of relying on depth sensors. Without using handcrafted features, we guide indoor scene modeling with feature maps extracted by fully convolutional networks. Three parallel fully convolutional networks are adopted to generate object instance masks, a depth map, and an edge map of the room layout. Based on these high-level features, support relationships between indoor objects can be efficiently inferred in a data-driven manner. Constrained by the support context, a global-to-local model matching strategy is followed to retrieve the whole indoor scene. We demonstrate that the proposed method can efficiently retrieve indoor objects including situations where the objects are badly occluded. This approach enables efficient semantic-based scene editing

Realistic texture synthesis for point-based fruitage phenotype.

Although current 3D scanner technology can acquire textural images from a point model, visible seams in the image, inconvenient data acquisition and occupancy of a large space during use are points of concern for outdoor fruit models. In this paper, an SPSDW (simplification and perception based subdivision followed by down-sampling weighted average) method is proposed to balance memory usage and texture synthesis quality using a crop fruit, such as apples, as a research subject for a point-based fruit model. First, the quadtree method is improved to make splitting more efficient, and a reasonable texton descriptor is defined to promote query efficiency. Then, the color perception feature is extracted from the image for all pixels. Next, an advanced sub-division scheme and down-sampling strategy are designed to optimize memory space. Finally, a weighted oversampling method is proposed for high-quality texture mixing. This experiment demonstrates that the SPSDW method preserves the mixed texture more realistically and smoothly and preserves color memory up to 94%, 84.7% and 85.7% better than the two-dimesional processing, truncating scalar quantitative and color vision model methods, respectively

Fusion Learning Conference 2023 - proceedings

Welcome to the 3rd annual Fusion Learning Conference at BU. The event provides a hub for the exchange of knowledge, pedagogical innovations, and cutting-edge research that shape the landscape of our learning and teaching. This year we are hosting the largest number of submissions to the conference and look forward to an exciting line up of guest speaker from IBM presenting on the influence of Artificial Intelligence on higher education; a BU panel of experts sharing their insight about some of the emerging themes in our learning and teaching and preparing our students for future of work; staff presentations and discussions including, student engagement, digital transformation, academic integrity, inclusive and sustainability in the curriculum design. I hope that you find this selection of posters and abstracts to be enlightening