5771284
Face relighting with radiance environment maps
A radiance environment map pre-integrates a constant surface reflectance with the lighting environment. It has been used to generate photo-realistic rendering at interactive speed. However, one of its limitations is that each radiance environment map can only render the object, which has the same surface reflectance as what it integrates. We present a ratio-image based technique to use a radiance environment map to render diffuse objects with different surface reflectance properties. This method has the advantage that it does not require the separation of illumination from reflectance, and it is simple to implement and runs at interactive speed. In order to use this technique for human face relighting, we have developed a technique that uses spherical harmonics to approximate the radiance environment map for any given image of a face. Thus we are able to relight face images when the lighting environment rotates. Another benefit of the radiance environment map is that we can interactively modify lighting by changing the coefficients of the spherical harmonics basis. Finally we can modify the lighting condition of one person's face so that it matches the new lighting condition of a different person's face image assuming the two faces have similar skin albedos.
215894941
Geometry-Driven Photorealistic Facial Expression Synthesis
Expression mapping (also called performance driven animation) has been a popular method for generating facial animations. A shortcoming of this method is that it does not generate expression detail...
15783652
Low bit-rate video streaming for face-to-face teleconference
Face-to-face video teleconferencing is very important for real time communication. Current teleconferencing applications use standard video codecs, such as MPEG 1/2/4, for the compression of face video. Either a high bandwidth is required for high quality video transmission, or the transmitted face video is blurred at low bitrates. We present a system for real-time coding of face video at low bit-rate. There are two main contributions. First, we improve the technique of long term memory prediction by selecting frames into the database in an optimal way. A new frame is selected into the database only when it is significantly different from those frames which are already in the database. In this way, the database can cover a wider range of images. Second, we incorporate prior knowledge about faces into the long term memory prediction framework. The prior knowledge includes: (1) facial motions are repetitive such that most of them can be reconstructed from multiple reference frames; (2) different components of the face and the background can tolerate different levels of error because of different perceptual importance. Experiments show that, at similar PSNR, the proposed system works much faster and achieves better visual quality than the standard H.264/JVT codec.
31830889
Real-Time Facial Expression Mapping for High Resolution 3D Meshes
We present a learning-based 3D facial expression mapping technique that preserves facial expression details and works in real time for even high resolution meshes. Our approach is inspired by a previously developed technique called deformation transfer [1]. The deformation transfer technique preserves facial expression details but its computational overhead makes it not suitable for real time applications. To accelerate computation, we use a piecewise linear function to represent the mapping from the direct motion (the difference between the expression face and the neutral face) to the motion obtained by the deformation transfer method. This piecewise linear function is learned offline from a small set of training data. The online computation is thus reduced to the evaluation of the piecewise linear functions which is significantly faster. As a result, we are able to perform real time expression mapping for even high resolution 3D meshes.
16274304
Face detection and tracking in video using dynamic programming
Face detection and tracking are important in video content analysis since the most important objects in most video are human beings. This paper proposes a new approach for combined face detection and tracking in video. The face detection algorithm is a fast template matching procedure using iterative dynamic programming (DP). Although the face detection algorithm is designed for frontal face, the same mechanism can also be applied to track non-frontal faces with online adapted face models. Due to the essence of template matching, the algorithm is capable of comparing the similarity among different faces, which makes it suitable for tracking the same face that occur at disjointed temporal locations in video. While the proposed face detection method provides comparable accuracy as the neural network based approach, it is much faster.
8930290
Data mining of gene expression changes in Alzheimer brain
Genome-wide transcription profiling is a powerful technique for studying the enormous complexity of cellular states. Moreover, when applied to disease tissue it may reveal quantitative and qualitative alterations in gene expression that give information on the context or underlying basis for the disease and may provide a new diagnostic approach. However, the data obtained from high-density microarrays is highly complex and poses considerable challenges in data mining. The data requires care in both pre-processing and the application of data mining techniques. This paper addresses the problem of dealing with microarray data that come from two known classes (Alzheimer and normal). We have applied three separate techniques to discover genes associated with Alzheimer disease (AD). The 67 genes identified in this study included a total of 17 genes that are already known to be associated with Alzheimer's or other neurological diseases. This is higher than any of the previously published Alzheimer's studies. Twenty known genes, not previously associated with the disease, have been identified as well as 30 uncharacterized expressed sequence tags (ESTs). Given the success in identifying genes already associated with AD, we can have some confidence in the involvement of the latter genes and ESTs. From these studies we can attempt to define therapeutic strategies that would prevent the loss of specific components of neuronal function in susceptible patients or be in a position to stimulate the replacement of lost cellular function in damaged neurons. Although our study is based on a relatively small number of patients (four AD and five normal), we think our approach sets the stage for a major step in using gene expression data for disease modeling (i.e. classification and diagnosis). It can also contribute to the future of gene function identification, pathology, toxicogenomics, and pharmacogenomics.
6770113
Image magnification method using joint diffusion
In this paper a new algorithm for image magnification is presented. Because linear magnification/interpolation techniques diminish the contrast and produce sawtooth effects, in recent years, many nonlinear interpolation methods, especially nonlinear diffusion based approaches, have been proposed to solve these problems. Two recently proposed techniques for interpolation by diffusion, forward and backward diffusion (FAB) and level-set reconstruction (LSR), cannot enhance the contrast and smooth edges simultaneously. In this article, a novel Partial Differential Equations (PDE) based approach is presented. The contributions of the paper include: firstly, a unified form of diffusion joining FAB and LSR is constructed to have all of their virtues; secondly, to eliminate artifacts of the joint diffusion, soft constraint takes the place of hard constraint presented by LSR; thirdly, the determination of joint coefficients, criterion for stopping time and color image processing are also discussed. The results demonstrate that the method is visually and quantitatively better than Bicubic, FAB and LSR.
38894685
A Strongly Polynomial Algorithm for the Inverse Shortest Arborescence Problem
Abstract In this paper an inverse problem of the weighted shortest arborescence problem is discussed. That is, given a directed graph G and a set of nonnegative costs on its arcs, we need to modify those costs as little as possible to ensure that T, a given v1 -arborescence of G, is the shortest one. It is found that only the cost of T needs modifying. An O(n3) combinatorial algorithm is then proposed. This algorithm also gives an optimal solution to the inverse weighted shortest path problem.
7502395
Dynamic image sequence analysis using fuzzy measures
In this paper, we present an image understanding system using fuzzy sets and fuzzy measures. This system is based on a symbolic object-oriented image interpretation system. We apply a simple, powerful three-dimensional (3-D) recursive filter to tracking moving objects in a dynamic image sequence. This filter has a time-varying 3-D frequency-planar passband that is adapted in a feedback system to automatically track moving objects. However, as objects in the image sequence are not well-defined and are engaged in dynamic activities, their shapes and trajectories in most cases can be described only vaguely. In order to handle these uncertainties, we use fuzzy measures to capture subtle variations and manage the uncertainties involved. This enables us to develop an image understanding system that produces a very natural output. We demonstrate the effectiveness of our system with complex real traffic scenes.