18528602
Outdoor Face Recognition Using Enhanced Near Infrared Imaging
In this paper, we present a robust and accurate system for outdoor (as well as indoor) face recognition, based on a recently developed enhanced near-infrared (ENIR) imaging device. Using a narrow band NIR laser generator instead of LED lights for active frontal illumination, the ENIR device can provide face images of good quality even under sunlight. Experiments show that the ENIR system performs similarly to the existing NIR system when used indoors, but outperforms it significantly outdoors especially under sunlight.
14656370
An Analysis-by-Synthesis Method for Heterogeneous Face Biometrics
Face images captured in different spectral bands, e.g. , in visual (VIS) and near infrared (NIR), are said to be heterogeneous. Although a person's face looks different in heterogeneous images, it should be classified as being from the same individual. In this paper, we present a new method, called face analogy , in the analysis-by-synthesis framework, for heterogeneous face mapping, that is, transforming face images from one type to another, and thereby performing heterogeneous face matching. Experiments show promising results.
144647
Recognizing Textual Relatedness with Predicate-Argument Structures
In this paper, we first compare several strategies to handle the newly proposed three-way Recognizing Textual Entailment (RTE) task. Then we define a new measurement for a pair of texts, called Textual Relatedness, which is a weaker concept than semantic similarity or paraphrase. We show that an alignment model based on the predicate-argument structures using this measurement can help an RTE system to recognize the Unknown cases at the first stage, and contribute to the improvement of the overall performance in the RTE task. In addition, several heterogeneous lexical resources are tested, and different contributions from them are observed.
16290950
Perceptually-motivated shape exaggeration
Image communication would appear more efficient if the visual cases of the concerned parts can be enhanced. One way to achieve this is by local shape exaggeration in rendering. In this paper, we present an interactive scheme for controllable local shape exaggeration. Our approach achieves local, direct, and consistent appearance enhancement by modifying the surface orientation in an intuitive and globally optimized manner with sparse user-specified constraints. Compared with previous approaches, the main contribution of this paper is the introduction of adaptive exaggeration function (AEF), which is capable of modulating the extent of detail enhancement to obtain a satisfactory shape exaggeration result. The AEF model is derived based on a series of experiments. We complement our new approach with a variety of examples, user studies, and provide comparisons with recent approaches.
3153096
On the Performance of Three Kinds of Channel Code Used in Turbo-BLAST
A MIMO system named Turbo-BLAST was introduced recently. We investigate the structure of Turbo- BLAST, and study its three kinds structures using different channel codes. Some necessary deductions and new structures are proposed: the decoding algorithm of trellis coded modulation (TCM) is modified to provide the detector with extrinsic information, and a new decoder structure for Turbo code is also given. Simulation results show that the structure using Turbo code can achieve better performance and faster convergence rate for high-order modulation. And the performance improvement of the structure using TCM is also obvious. Since TCM can bring high spectral efficiency, it would be useful to apply TCM in Turbo-BLAST.
34764255
Mixed Reality-Mediated Collaborative Design System: Concept, Prototype, and Experimentation
This paper introduces a Mixed Reality-mediated Collaborative design system, named MR-Collab, which combines Mixed Reality (MR), Augmented Reality (AR) and various channels of communication technologies. The concept and system of MR-Collabare developed based on the Benford's Mixed-Reality boundaries theory. This paper presents how this theory is used as a tool to analyze the system framework and guide the design of the MR-Collabsystem. The technique details of prototype and application scenario of this system are also elaborated in the paper. The system, MR-Collab, is designed in the purpose of facilitating collaboration between distributed users through the Mixed Reality environment. Experimentation that can measure the correlations between the design performance/behaviors with the increased degree of co-presence is also planned in this paper.
8634013
Fast, Sub-pixel Antialiased Shadow Maps
Solving aliasing artifacts is an essential problem in shadow mapping approaches. Many works have been proposed, however, most of them focused on removing the texel-level aliasing that results from the limited resolution of shadow maps. Little work has been done to solve the pixel-level shadow aliasing that is produced by the rasterization on the screen plane. In this paper, we propose a fast, sub-pixel antialiased shadowing algorithm to solve the pixel aliasing problem. Our work is based on the alias-free shadow maps, which is capable of computing accurate per-pixel shadow, and only incurs little cost to extend to sub-pixel accuracy. Instead of direct supersampling the screen space, we take facets to approximate pixels in shadow testing. The shadowed area of one facet is rapidly evaluated by projecting blocker geometry onto a supersampled 2D occlusion mask with bitmasks fusion. It provides a sub-pixel occlusion sampling so as to capture fine shadow details and features. Furthermore, we introduce the silhouette mask map that limits visibility evaluation to pixels only on the silhouette, which greatly reduces the computation cost. Our algorithm runs entirely on the GPU, achieving real-time performance and is an order of magnitude faster than the brute-force supersampling method to produce comparable 32× antialiased shadows.