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.
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.
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.
31519303
Data-Driven Facial Feature Morphing for 3D Face Synthesis
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.
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.
15044843
Learning from facial aging patterns for automatic age estimation
Age Specific Human-Computer Interaction (ASHCI) has vast potential applications in daily life. However, automatic age estimation technique is still underdeveloped. One of the main reasons is that the aging effects on human faces present several unique characteristics which make age estimation a challenging task that requires non-standard classification approaches. According to the speciality of the facial aging effects, this paper proposes the AGES (AGing pattErn Subspace) method for automatic age estimation. The basic idea is to model the aging pattern, which is defined as a sequence of personal aging face images, by learning a representative subspace. The proper aging pattern for an unseen face image is then determined by the projection in the subspace that can best reconstruct the face image, while the position of the face image in that aging pattern will indicate its age. The AGES method has shown encouraging performance in the comparative experiments either as an age estimator or as an age range estimator.
15941574
Organizational Adaptative Behavior: The Complex Perspective of Individuals-Tasks Interaction
Organizations with different organizational structures have different organizational behaviors when responding environmental changes. In this paper, we use a computational model to examine organizational adaptation on four dimensions: Agility, Robustness, Resilience, and Survivability. We analyze the dynamics of organizational adaptation by a simulation study from a complex perspective of the interaction between tasks and individuals in a sales enterprise. The simulation studies in different scenarios show that more flexible communication between employees and less hierarchy level with the suitable centralization can improve organizational adaptation.
2325109
Exploiting upper and lower bounds in top-down query optimization
System R's bottom-up query optimizer architecture forms the basis of most current commercial database managers. The paper compares the performance of top-down and bottom-up optimizers, using the measure of the number of plans generated during optimization. Top down optimizers are superior according to this measure because they can use upper and lower bounds to avoid generating groups of plans. Early during the optimization of a query, a top-down optimizer can derive upper bounds for the costs of the plans it generates. These bounds are not available to typical bottom-up optimizers since such optimizers generate and cost all subplans before considering larger containing plans. These upper bounds can be combined with lower bounds, based solely on logical properties of groups of logically equivalent subqueries, to eliminate entire groups of plans from consideration. We have implemented such a search strategy, in a top-down optimizer called Columbia. Our performance results show that the use of these bounds is quite effective, while preserving the optimality of the resulting plans. In many circumstances this new search strategy is even more effective than heuristics such as considering only left deep plans.
4832713
Heteroscedastic Probabilistic Linear Discriminant Analysis with Semi-supervised Extension
Linear discriminant analysis (LDA) is a commonly used method for dimensionality reduction. Despite its successes, it has limitations under some situations, including the small sample size problem, the homoscedasticity assumption that different classes have the same Gaussian distribution, and its inability to produce probabilistic output and handle missing data. In this paper, we propose a semi-supervised and heteroscedastic extension of probabilistic LDA, called S2HPLDA, which aims at overcoming all these limitations under a common principled framework. Moreover, we apply automatic relevance determination to determine the required dimensionality of the low-dimensional space for dimensionality reduction. We empirically compare our method with several related probabilistic subspace methods on some face and object databases. Very promising results are obtained from the experiments showing the effectiveness of our proposed method.