8951856
Model-based head pose tracking with stereovision
We present a robust model-based stereo head tracking algorithm that operates in real time on a commodity PC. The use of an individualized three-dimensional head model, coupled with the epipolar constraint from the stereo image pair greatly improves the robustness of the tracking. Experimental results have shown that our method is able to track all the six degrees of freedom of the rigid part of head motions, over an extended period of time, in the presence of large angular and translational head motions, partial occlusions, and/or dramatic facial expression changes. Applications include human-computer interaction and eye-gaze correction for videoconferencing.
5156351
Model-based bundle adjustment with application to face modeling
We present a new model-based bundle adjustment algorithm to recover the 3D model of a scene/object from a sequence of images with unknown motions. Instead of representing scene/object by a collection of isolated 3D features (usually points), our algorithm uses a surface controlled by a small set of parameters. Compared with previous model-based approaches, our approach has the following advantages. First instead of using the model space as a regularizer we directly use it as our search space, thus resulting in a more elegant formulation with fewer unknowns and fewer equations. Second, our algorithm automatically associates tracked points with their correct locations on the surfaces, thereby eliminating the need for a prior 2D-to-3D association. Third, regarding face modeling, we use a very small set of face metrics (meaningful deformations) to parameterize the face geometry, resulting in a smaller search space and a better posed system. Experiments with both synthetic and real data show that this new algorithm is faster, more accurate and more stable than existing ones.
6930232
Expressive expression mapping with ratio images
Facial expressions exhibit not only facial feature motions, but also subtle changes in illumination and appearance (e.g., facial creases and wrinkles). These details are important visual cues, but they are difficult to synthesize. Traditional expression mapping techniques consider feature motions while the details in illumination changes are ignored. In this paper, we present a novel technique for facial expression mapping. We capture the illumination change of one person's expression in what we call an expression ratio image (ERI). Together with geometric warping, we map an ERI to any other person's face image to generate more expressive facial expressions.
16465387
Rapid modeling of animated faces from video
Generating realistic 3D human face models and facial animations has been a persistent challenge in computer graphics. We have developed a system that constructs textured 3Dface models from videos with minimal user interaction. Our system takes images andvideo sequences of a face with an ordinary video camera. After five manual clicks ontwo images to tell the system where the eye corners, nose top and mouth corners are, thesystem automatically generates a realistic looking 3D human head model and the constructed model can be animated immediately. A user with a PC and an ordinary camera can use our system to generate his/her face model in a few minutes. Copyright © 2001 John Wiley & Sons, Ltd.
8907053
Feature-Based Facial Expression Recognition: Sensitivity Analysis and Experiments with A Multilayer Perceptron
In this paper, we report our experiments on feature-based facial expression recognition within an architecture based on a two-layer perceptron. We investigate the use of two types of features extracted from face images: the geometric positions of a set of fiducial points on a face, and a set of multiscale and multiorientation Gabor wavelet coefficients at these points. They can be used either independently or jointly. The recognition performance with different types of features has been compared, which shows that Gabor wavelet coefficients are much more powerful than geometric positions. Furthermore, since the first layer of the perceptron actually performs a nonlinear reduction of the dimensionality of the feature space, we have also studied the desired number of hidden units, i.e. the appropriate dimension to represent a facial expression in order to achieve a good recognition rate. It turns out that five to seven hidden units are probably enough to represent the space of facial expressions. Then, we have investigated the importance of each individual fiducial point to facial expression recognition. Sensitivity analysis reveals that points on cheeks and on forehead carry little useful information. After discarding them, not only the computational efficiency increases, but also the generalization performance slightly improves. Finally, we have studied the significance of image scales. Experiments show that facial expression recognition is mainly a low frequency process, and a spatial resolution of 64 pixels × 64 pixels is probably enough.
9407873
Linear combination representation for outlier detection in motion tracking
In this paper we show that Ullman and Basri's linear combination (LC) representation, which was originally proposed for alignment-based object recognition, can be used for outlier detection in motion tracking with an affine camera. For this task LC can be realized either on image frames or feature trajectories, and therefore two methods are developed which we call linear combination of frames and linear combination of trajectories. For robust estimation of the linear combination coefficients, the support vector regression (SVR) algorithm is used and compared with the RANSAC method. SVR based on quadratic programming optimization can efficiently deal with more than 50 percent outliers and delivers more consistent results than RANSAC in our experiments. The linear combination representation can use SVR in a straightforward manner while previous factorization-based or subspace separation methods cannot. Experimental results are presented using real video sequences to demonstrate the effectiveness of our LC+SVR approaches, including a quantitative comparison of SVR and RANSAC.
6153081
Zero-Error Capacity for Models with Memory and the Enlightened Dictator Channel
Summary form only given. We present a general class of "combinatorial" 0-error capacity problems with the "memory" covering known and many new cases. This class can be incorporated into a model of channels with memory. W analyse a seemingly basic channel in this class, which we call the "dictator channel". Clearly, a dictator always follows his own opinion. However, we speak of an enlightened dictator, if he responds to the unanimous vote of the people against his opinion to the degree, in this case he reaches a decision by coin tossing.
29303828
Parameter estimation techniques: a tutorial with application to conic fitting
Almost all problems in computer vision are related in one form or another to the problem of estimating parameters from noisy data. In this tutorial, we present what is probably the most commonly used techniques for parameter estimation. These include linear least-squares (pseudo-inverse and eigen analysis); orthogonal least-squares; gradient-weighted least-squares; bias-corrected renormalization; Kalman filtering; and robust techniques (clustering, regression diagnostics, M-estimators, least median of squares). Particular attention has been devoted to discussions about the choice of appropriate minimization criteria and the robustness of the different techniques. Their application to conic fitting is described.
18878687
Directional Coherence Interpolation For Three-Dimensional Gray-Level Images
A novel three-dimensional gray-level interpolation method called the Directional Coherence Interpolation (DCI) is presented in the paper. The principal advantage of the proposed approach is that it leads to significantly higher visual quality in 3D rendering when compared with traditional image interpolation methods. The basis of DCI is a form of directional image-space coherence. DCI interpolates the missing image data along the maximum coherence directions (MCD), which are estimated from the local image intensity yet constrained by a generic smoothness term. In order to further improve both the algorithm efficiency and robustness, we also propose to apply a pyramidal search strategy for MCD estimation. This coarse-to-fine scheme requires less computation time by starting with the reduced amount of data and propagating searching results to finer resolutions. DCI can incorporate image shape and structure information without the prior requirement of explicit representation of object boundary/surface. Extensive experiments were performed on both synthetic and real medical images to evaluate the proposed approaches. The experimental results show that the proposed methods are able to handle general object interpolation, while achieving both accuracy and efficiency in interpolation compared with the existing techniques.
206417245
Estimation of Displacements from Two 3-D Frames Obtained From Stereo
A method for estimating 3D displacements from two stereo frames is presented. It is based on the hypothesize-and-verify paradigm used to match 3D line segments between the two frames. In order to reduce the complexity of the method, an assumption is made that objects are rigid. The formulate a set of complete rigidity constraints for 3D line segments and integrate the uncertainty of measurements in this formation. The hypothesize-and-verify stages of the method use an extended Kalman filter to produce estimates of the displacements and of their uncertainty. The algorithm is shown to work on indoor and natural scenes. It is also shown to be easily extended to the case in which several mobile objects are present. The method is quite robust, fast, and has been thoroughly tested on hundreds of real stereo frames. >
11664234
Secure Name Service: A Framework for Protecting Critical Internet Resources
We propose a novel Secure Name Service (SNS) framework for protecting critical Internet resources from unauthorized accesses, denial of service (DoS) and other attacks. The key idea is to enforce packet-origin authentication through resource virtualization and utilize dynamic name binding for protecting servers under attacks and improving service availability. Different from static network-level security schemes such as IPsec and VPN, SNS is able to dynamically bind the names of critical resources at the service level, which allows us to actively protect the service resources through a distributed filtering mechanism built on authenticated packet forwarding paths. Our prototype implementation of authenticated packet forwarding components on Pentium 4 Linux machines demonstrates that regular Linux platforms are sufficient to support SNS authenticated packet forwarding on 100Mbps or lGbps LANs.