15799724
An On-Off Queue Control Mechanism for Scalable Video Streaming over the IEEE 802.11e WLAN
In this paper, we study the issue of scalable video streaming over IEEE 802.11e EDCA WLANs. Our basic idea is to control the number of "active" nodes on the channel in order to reduce collisions under heavy traffic conditions. Specifically, we propose a distributed on-off queue control (OOQC) mechanism, which is designed to maintain high network throughput while keeping packet loss due to collision as low as possible. A low priority early drop (LPED) method is also employed to drop the packets at the queue according to packet relative priority index (RPI) provided by scalable video coding. Simulation results show that our proposed OOQC scheme significantly outperforms EDCA in received video quality.
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.
31519303
Data-Driven Facial Feature Morphing for 3D Face Synthesis
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.
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.
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.
62060172
Multi-octagon-grid search algorithm for fast motion estimation
The UMHexagonS algorithm has been accepted for the possible implementation of the block motion estimation process in the H.264 video coding standard due to its high accuracy and low computational requirement. In this paper, a new algorithm is proposed, which improves on the UMHexagonS algorithm in three aspects. Firstly, a new prediction vector is added for avoiding being trapped in a local minimum. Secondly, the 5times5 full-search is replaced with an octagon search and possibly two small diamond searches to reduce the computational requirement. Thirdly, the multi-hexagon-grid search is changed to a multi-octagon-grid search to both reduce the computational complexity and better catch the direction of the optimal vector. Simulation results demonstrate that the proposed algorithm can reduce five to ten percent of the computational complexity of the UMHexagonS algorithm without loss of its accuracy.
14113669
Performance Comparison Between Statistical-Based and Direct Data Domain STAPs
In this paper the performances of two space-time adaptive processing (STAP), namely statistical-based methods and the direct data domain least squares (D3LS) method, are compared. The number of secondary or training data needed in the processing is a major concern in many applications. In the situation that the radar platform moves relatively fast, the smallest number of secondary data is preferred. While the statistical-based methods require training data in estimating the interference covariance matrix, the D3LS does not. The D3LS utilizes the interference information in a space-time snapshot under test itself in canceling this interference. The goal of this paper is to evaluate the performance of these two approaches by comparing the accuracy of the signal amplitude estimation when the number of training data is varied
4846997
Semi-supervised Discriminant Analysis Via CCCP
Linear discriminant analysis (LDA) is commonly used for dimensionality reduction. In real-world applications where labeled data are scarce, LDA does not work very well. However, unlabeled data are often available in large quantities. We propose a novel semi-supervised discriminant analysis algorithm called SSDA$_{\mathit{CCCP}}$. We utilize unlabeled data to maximize an optimality criterion of LDA and use the constrained concave-convex procedure to solve the optimization problem. The optimization procedure leads to estimation of the class labels for the unlabeled data. We propose a novel confidence measure for selecting those unlabeled data points with high confidence. The selected unlabeled data can then be used to augment the original labeled data set for performing LDA. We also propose a variant of SSDA$_{\mathit{CCCP}}$, called M-SSDA$_{\mathit{CCCP}}$, which adopts the manifold assumption to utilize the unlabeled data. Extensive experiments on many benchmark data sets demonstrate the effectiveness of our proposed methods.
17429523
A Novel Trust-based Cooperative Node Selection Scheme in Wireless Sensor Networks
For communication between the cluster head node (CHN) and the distant data fusion center (DFC) with the cooperation of intra-cluster nodes in wireless sensor networks (WSNs), reliable handling of packets by the cooperative node (CN) is difficult to ensure. In this paper, we propose a novel CN selection scheme based on trust for WSNs. This scheme can choose one of high trust nodes to assist in the transmission of CHN, which aims to improve the transmission performance over cooperative communication in the presence of potential malicious nodes. First, we establish a trust model to improve the reliability of transmission by CN in WSNs, which is based on both the direct trust and the indirect trust of nodes. Then the CHN selects a node based on the proposed trust model to aid the CHN in transmission. Simulation results show that the proposed scheme can mitigate the impact of the potential malicious nodes on transmission performance and the simulation results also demonstrate the efficiency of the proposed scheme.
37152915
Image Disorientation Auto-Recovery
Automatically detecting and correcting disoriented image frames in a content-related image sequence is a problem that must be addressed in many image and video applications. In this paper, we give a robust feature-based algorithm to efficiently detect and adjust the disorientation of images. Keyword image orientation, crop, Robert edge detection, line feature, Hough transformation.