43457446
Synthesis of facial expressions using a 3D anatomical model
In this paper we propose an individualized 3D facial model constructed from the anatomical perspective for realistic facial expression synthesis. Our model incorporates a physically-based approximation to facial skin tissue, a set of anatomically-motivated facial muscle actuators and underlying skull structure. The skin is modeled as a multi-layer mass-spring lattice by taking into account the nonlinear stress-strain relationship of the real skin. The 3D face model incorporates a skull structure which extends the scope of facial motion and facilitates facial muscle definition. The automatic facial muscle construction is achieved by using an efficient muscle mapping approach that ensures different muscles to be located at the anatomically correct positions between the skin and skull layers. For computational efficiency, we devise a semi-implicit integration method to numerically solve the governing dynamics. The dynamic facial animation algorithm runs at an interactive rate with realistic facial expressions to be synthesized.
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.
5849129
A new physical model with multilayer architecture for facial expression animation using dynamic adaptive mesh
This paper presents a new physically-based 3D facial model based on anatomical knowledge which provides high fidelity for facial expression animation while optimizing the computation. Our facial model has a multilayer biomechanical structure, incorporating a physically-based approximation to facial skin tissue, a set of anatomically-motivated facial muscle actuators, and underlying skull structure. In contrast to existing mass-spring-damper (MSD) facial models, our dynamic skin model uses the nonlinear springs to directly simulate the nonlinear visco-elastic behavior of soft tissue and a new kind of edge repulsion spring is developed to prevent collapse of the skin model. Different types of muscle models have been developed to simulate distribution of the muscle force applied on the skin due to muscle contraction. The presence of the skull advantageously constrain the skin movements, resulting in more accurate facial deformation and also guides the interactive placement of facial muscles. The governing dynamics are computed using a local semiimplicit ODE solver. In the dynamic simulation, an adaptive refinement automatically adapts the local resolution at which potential inaccuracies are detected depending on local deformation. The method, in effect, ensures the required speedup by concentrating computational time only where needed while ensuring realistic behavior within a predefined error threshold. This mechanism allows more pleasing animation results to be produced at a reduced computational cost.
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.
15173958
Reanimating real humans: automatic reconstruction of animated faces from range data
Advances in 3D scanning technology have enabled automatic capture of complex 3D models such as human faces with highly detailed surfaces. However, the range data cannot be used easily for animatable face modeling due to the absence of functional animation structure and dense surface data. The paper presents an automatic facial model adaptation algorithm for reconstruction of animatable individualized 3D facial models from range data. A generic model that represents both the face shape and anatomical structure serves as the starting point for the adaptation algorithm. The global adaptation transforms the generic model to align it with the scan data in the 3D space based on measurements between a set of 3D landmarks. The local adaptation then deforms the skin mesh of the generic model to fit all of its vertices to the scan surface. The underlying muscle structure is automatically adapted and facial texture is transferred. The reconstructed 3D face resembles the shape and color of a real individual and can be animated immediately with muscle parameters.
39711298
Data-Driven Feature Control Models for Creating Virtual Faces
This paper presents a novel data-driven method for creating realistic face models based on estimated high-level feature control models. Our method takes as examples 3D face scans. By bringing scanned models into full correspondence with a model fitting approach, we apply principal component analysis (PCA) to the exemplar shapes of each facial feature to build a shape space. We compute a set of face anthropometric measurements to parameterize example feature shapes in the measurement spaces. Using the PCA coefficients as a compact shape representation, we approach the shape synthesis problem by forming scattered data interpolation functions that are devoted to the generation of desired shape by taking the anthropometric parameters as input. The correspondence among all exemplar textures is obtained by parameterizing a 3D generic mesh over a 2D image domain. The new feature texture with desired attributes is synthesized by interpolating the example textures.
17285338
A reputation-chain trust model for the semantic Web
Trust plays a central role for efficient and secure interactions on the semantic Web. Nowadays, more and more research has focused on this topic. In this paper, we introduce RCSW, a reputation-chain trust model for the semantic Web. We illustrate the basic definitions and mechanisms of RCSW and present the algorithm to calculate trust ratings through the chain of the trust network. RCSW incorporates pairwise trust values and reliable factors of acquaintances and constructs an edge-weighted graph to calculate trust ratings. We also define classes of trust functions to allow users to individualize their trust calculation. Our proposed model can deal with trust management effectively and can quickly adapt to the changing environment.
2479481
Gene Regulatory Network Construction Using Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM)
Discovering gene relationship from gene expression data is a hot topic in the post-genomic era. In recent years, Bayesian network has become a popular method to reconstruct the gene regulatory network due to the statistical nature. However, it is not suitable for analyzing the time-series data and cannot deal with cycles in the gene regulatory network. In this paper we apply the dynamic Bayesian network to model the gene relationship in order to overcome these difficulties. By incorporating the structural expectation maximization algorithm into the dynamic Bayesian network model, we develop a new method to learn the regulatory network from the S. Cerevisiae cell cycle gene expression data. The experimental results demonstrate that. the accuracy of our method outperforms the previous work.
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.
30553314
A new algorithm based on auxiliary virtual topology for sub-path protection in WDM optical networks
This paper proposes a new survivable algorithm named sub-path protection based on auxiliary virtual topology (SPAVT) to tolerate the single-link failure in WDM optical networks. First, according to the protection-switching time constraint, SPAVT searches multiple pairs of primary and backup paths for each node pair in the network by the off-line manner, and then map these paths to the virtual topology. When a connection request arrives, SPAVT only needs to run one time of the Dijkstra's algorithm to search a virtual route in virtual topology, where the route may consist of multiple pairs of sub-paths, to meet the protection-switching time constraint. Then, according to the shared resources policy, SPAVT chooses an optimal pair of sub-paths. Simulation results show that SPAVT has smaller blocking probability and lower time complexity than conventional algorithms.
31437218
Choosing Business Collaborators Using Computing Intelligence Methods
Inter-firm collaboration has become a common feature of the developing international economy. Firms as well as the nations have more relationships with each other. Even relatively closed economies or industries are becoming more open, Australia and China are examples of this case. The benefits generated from collaboration and the motivations to form collaboration are investigated by some researchers. However, the widely studied relationships between collaboration and profits are based on tangible assets and turnovers whereas most intangible assets and benefits are neglected during the economic analysis. In the present paper, two methods, naive Bayes and neural network, from computing intelligence are used to study the benefits acquired from collaboration. These two methods are used to learn the relationship and make prediction for a specified collaboration. The proposed method has been applied to a practical case of WEMOSOFT, an independent development department under MOBOT. The predication accuracies are 87.18% and 92.31%, for neural network and naive Bayes, respectively. Experimental result demonstrates that the proposed method is an effective and efficient way to prediction the benefit of collaboration and choose the appropriate collaborator.