16395245
Hierarchical face modeling and fast 3D facial expression synthesis
This paper presents a new hierarchical facial model that conforms to the human anatomy for realistic and fast 3D facial expression synthesis. The facial model has a skin/muscle/skull structure. The deformable skin model uses a kind of nonlinear spring to directly simulate the nonlinear visco-elastic behavior of soft tissue, and a new kind of edge repulsion spring is developed to prevent model collapse. The incorporation of the skull extends the scope of facial motion and facilitates facial muscle construction. The construction of facial muscles is achieved by using an efficient muscle mapping approach that ensures different muscles to be located at the anatomically correct positions. For computational efficiency, we devise an adaptive simulation algorithm which uses either a semi-implicit integration scheme or a quasi-static solver to compute the relaxation by traversing the designed data structures in a breadth-first order. The algorithm runs in real-time and has successfully synthesized realistic facial expressions.
20139173
Muscle-driven modeling of wrinkles for 3D facial expressions
Facial expression animation considering wrinkle formation is an aspiring goal and a challenging task. This paper presents a new geometric wrinkle model that is defined according to facial muscle anatomy for efficient simulation of dynamic wrinkles within expressions. Our method is applied to an anatomy-based face model with a multi-layer structure of skin, muscles, and skull. The location and orientation of the wrinkles are automatically determined based on muscle contraction and its influence on the skin. Corresponding to two types of facial muscles, the geometric wrinkle model governs evolution of wrinkle amplitude in the local deformed face regions. It provides intuitive parameters for easy control over wrinkle characteristics by taking into account the properties of real wrinkles. Results show that this method enables realistic wrinkles synchronized with facial movements to be dynamically simulated and rendered at an interactive rate.
17517047
From range data to animated anatomy-based faces: a model adaptation method
This paper presents a new method for reconstructing animated, anatomy-based facial models of individuals from range data with minimal manual intervention. A prototype model with a multi-layer skin-muscle-skull structure serves as the starting point for our method. After the global adaptation, the skin mesh of the prototype model is represented as a dynamic deformable model which is deformed to fit scanned data according to internal force stemming from the elastic properties of the surface and external forces produced from the scanned data points and features. The underlying muscle layer that consists of three types of facial muscles is automatically adapted. According to the adapted skin and muscle structures, a set of automatically generated skull feature points is transformed to drive a volume morphing of the template skull model for skull fitting. The reconstructed model realistically reproduces the shape and features of a specific person and can be animated instantly.
59703933
Anatomy-based 3D facial modeling for expression animation
In this paper we propose a new hierarchical 3D facial model that conforms to the human facial anatomy for realistic facial expression animation. The facial model has a hierarchical biomechanical structure, incorporating a physically-based approximation to facial skin tissue, a set of anatomically-motivated facial muscle actuators and underlying skull structure. The deformable skin model has multi-layer structure to approximate different types of soft tissue. It takes into account the nonlinear stress-strain relationship of the skin and the fact that soft tissue is almost incompressible. Different kinds of muscle models have been developed to simulate the distribution of the muscle force on the skin due to muscle contraction. By the presence of the skull model, our facial model takes advantage of both more accurate facial deformation and the consideration of facial anatomy during the interactive definition of facial muscles. Under the muscular force, the deformation of the facial skin is evaluated by solving the governing dynamic equation numerically. To improve computational efficiency, we use a localized, semi-implicit integration method which allows a larger time step to be taken in the simulation while retaining stability. The dynamic facial animation algorithm runs at an interactive rate with flexible and realistic facial expressions to be generated.
45254253
A physically-based model for real-time facial expression animation
In this paper we propose a physically-based 3D dynamic facial model based on anatomical knowledge for facial expression animation. The facial model incorporates a physically-based approximation to facial skin and a set of anatomically-motivated facial muscles. The skin model is established through the use of a mass-spring system with nonlinear springs which simulate the elastic dynamics of a real facial skin. Facial muscle models are developed to emulate facial muscle contraction. Lagrangian mechanics governs the dynamics, dictating the deformation of facial surface in response to muscle forces. The dynamic facial modeling algorithm runs at interactive rate with continuous 3D display on a graphics workstation. Using our system, we can effectively synthesize realistic facial expressions and analyze tile relationship between facial surface deformation and the activation of underlying facial muscles.
40211124
Real-time physically-based facial expression animation using mass-spring system
We propose a physically-based approach based on anatomical knowledge for real-time facial expression animation. The facial model incorporates a physically-based approximation to facial skin and a set of anatomically-motivated facial muscles. The skin is modeled by a mass-spring system with nonlinear springs which have a biphasic stress-strain relationship to simulate the elastic dynamics of real facial skin. Facial muscles are modeled as forces deforming the spring mesh. Based on the action units (AUs) of the facial action coding system (FACS), various expressions can be generated by a combination of contractions of a set of facial muscles. Lagrangian mechanics governs the dynamics, dictating the deformation of the facial surface in response to muscle forces. Simulation results show real-time facial deformation as well as realistic expression animation.
31009913
Synthesis of 3D faces using region-based morphing under intuitive control
This paper presents a new region-based method for automatically synthesizing varied, natural looking 3D human face models by morphing local facial features according to intuitive control parameters. We automatically compute a one-to-one vertex correspondence among the unregistered face scans in a large database by deforming a generic mesh to fit the specific person's face geometry in a global-to-local fashion. With the obtained correspondence, we transform the generated data sets of feature shapes into vector space representations. We parameterize the example models using the face anthropometric measurements that reflect the facial physical structure, and predefine the interpolation functions for the parameterized example models based on radial basis functions. At runtime, the interpolation functions are evaluated to efficiently generate the appropriate feature shape by taking the anthropometric parameters as input. We use a shape blending approach for generating a seamlessly deformed mesh around the feature region boundary. The correspondence among all example textures is established by parameterizing the 3D generic mesh over a 2D image domain. The new feature texture with desired attributes is synthesized by interpolating the example textures. Our 3D face synthesis method has several advantages: (1) it regulates the naturalness of synthesized faces, maintaining the quality existing in the real face examples; (2) the region-based morphing and comprehensive face shape and texture control parameters allow more diverse faces to be generated readily; and (3) the automatic runtime face synthesis is efficient in time complexity and performs fast. Copyright © 2006 John Wiley & Sons, Ltd.
9462041
HPtaa database-potential target genes for clinical diagnosis and immunotherapy of human carcinoma
Tumor-associated antigens (TAAs) have been the most actively employed targets in the clinical diagnosis and treatment of human carcinoma, such as PSA in the diagnosis of prostate cancer and NY-ESO-1 in the immunotherapy of melanoma and other cancers. However, identification of TAAs has often been hampered by the complicated and laborsome laboratory procedures. In order to accelerate the process of tumor antigen discovery, and thereby improve diagnosis and treatment of human carcinoma, we have made an effort to establish a publicly available Human Potential Tumor Associated Antigen database (HPtaa) with potential TAAs identified by in silico computing (http://www.hptaa.org). Tumor specificity was chosen as the core of tumor antigen evaluation, together with other relevant clues. Various platforms of gene expression, including microarray, expressed sequence tag and SAGE data, were processed and integrated by several penalty algorithms. A total of 3518 potential TAAs have been included in the database, which is freely available to academic users. As far as we know, this database is the first one addressing human potential TAAs, and the first one integrating various kinds of expression platforms for one purpose.
12263549
Tree-guided Bayesian inference of population structures
MOTIVATION
Inferring population structures using genetic data sampled from a group of individuals is a challenging task. Many methods either consider a fixed population number or ignore the correlation between populations. As a result, they can lose sensitivity and specificity in detecting subtle stratifications. In addition, when a large number of genetic markers are used, many existing algorithms perform rather inefficiently.


RESULT
We propose a new Bayesian method to infer population structures using multiple unlinked single nucleotide polymorphisms (SNPs). Our approach explicitly considers the population correlation through a tree hierarchy, and treat the population number as a random variable. Using both simulated and real datasets of worldwide samples, we demonstrate that an incorporated tree can consistently improve the power in detecting subtle population stratifications. A tree-based model often involves a large number of unknown parameters, and the corresponding estimation procedure can be highly inefficient. We further implement a partition method to analytically integrate out all nuisance parameters in the tree. As a result, our method can analyze large SNP datasets with significantly improved convergence rate.


AVAILABILITY
http://www.stat.psu.edu/~yuzhang/tips.tar.
8300404
Modeling Internet Link Delay Based on Measurement
Understanding Internet link delay is an important key of taking full advantage of Internet resources. In this paper, we find that the link delay follows Gammadistribution using Maximum Likelihood Estimation based on data measured in a large-scale network. The correlations between the link delay and the edge load, the node degree, and the betweenness are analyzed respectively. The link delay distribution parameters for different ranges of edge load are calculated. We findthat the edge load is correlated positively with the shape parameter of link delay Gamma distribution and negatively with the scale parameter.
40389264
Application of Efficient Numerical Methods in Solution of Ordinary Differential Equations for Modeling Electrical Activity in Cardiac Cells
There is a large number of ordinary differential equations (ODEs) characterize the electrical behavior generated by ionic movements in human myocardial cell. In this paper, several approaches were investigated in order to improve the efficiency of solving the ODE systems for ten Tusscher et al.’s ionic model of human ventricular tissue. By using non-standard finite difference (NSFD) scheme, the stiffness of the ODEs system will be successfully reduced, so a larger step-size can be used. A popular multi-step method called backward differentiation formulation (BDF) was also incorporated into the computational model for testing the largest possible time steps. The results show that NSFD can be as much as 10 times more efficient than standard forward Euler in single cell model simulation while maintaining an acceptable level of accuracy. The investigation of BDF method shows that a large step size is not recommended for the single cell simulation application. All solvers were coupled to the partial differential equations for the complete simulation of heart tissue, and such computation scheme may be a good calculation technique in heart modeling and simulation.