Fast Omnidirectional 3D Scene Acquisition with an Array of Stereo Cameras
We present an omnidirectional 3D acquisition system based on a mobile array of high-resolution consumer digital SLR cameras that automatically capture high dynamic range stereo pairs across a full 360-degree panorama. The stereo pairs are augmented with a time-varying lighting pattern created using standard photographic flashes, lenses, and patterned slides. Spacetime stereo techniques are used to generate 3D range images with corresponding color data from the HDR photographs. The multiple range images are aligned with egomotion estimation and ICP registration techniques, and volumetric merging and color texturing algorithms allow the rapid creation of complete 3D models. The resulting system compares favorably with other state of the art 3D acquisition technologies in the resolution and quality of its output, and can be faster and less expensive than 3D laser scanners for digitizing large 3D scenes such as building interiors.

title: Computation on Programmable Graphics Hardware
abstract: GPUs have evolved into powerful and flexible streaming processors with fully programmable floating-point pipelines and tremendous aggregate computational power and memory bandwidth. With these advances, modern GPUs can now perform more functions than the specific graphics computations for which they were designed. This article describes approaches to using GPU processing power to accelerate traditionally CPU-based tasks. We discuss some important characteristics of algorithms that make them good candidates for GPU acceleration. We discuss a specific GPU image-processing application that is a common postprocess for many physically based rendering systems.

title: Interactive Time-Dependent Tone Mapping Using Programmable Graphics Hardware

title: All-frequency interactive relighting of translucent objects with single and multiple scattering
abstract: We present a technique, based on precomputed light transport, for interactive rendering of translucent objects under all-frequency environment maps. We consider the complete BSSRDF model proposed by Jensen et al. [2001]. which includes both single and diffuse multiple scattering components. The challenge is how to efficiently precompute all-frequency light transport functions due to subsurface scattering. We apply the two-pass hierarchical technique by Jensen et al. [2002] in the space of non-linearly approximated transport vectors, which allows us to efficiently evaluate transport vectors due to diffuse multiple scattering. We then include an approximated single scattering term in the precomputation, which previous interactive systems have ignored. For an isotropic phase function, this approximation produces a diffuse transport vector per vertex, and is combined with the multiple scattering component. For a general phase function, we introduce a technique from BRDF rendering to factor the phase function using a separable decomposition to allow for view-dependent rendering. We show that our rendering results qualitatively match the appearance of translucent objects, achieving a high level of realism at interactive rates.

title: Bidirectional Importance Sampling for Unstructured Direct Illumination
abstract: Recent research in bidirectional importance sampling has focused primarily on structured illumination sources such as distant environment maps, while unstructured illumination has received little attention. In this paper, we present a method for bidirectional importance sampling of unstructured illumination, allowing us to use the same method for sampling both distant as well as local/indirect sources. Building upon recent work in [WFA*05], we model complex illumination as a large set of point lights. The subsequent sampling process draws samples only from this point set. We start by constructing a piecewise constant approximation for the lighting using an illumination cut [CPWAP08]. We show that this cut can be used directly for illumination importance sampling. We then use BRDF importance sampling followed by sample counting to update the cut, resulting in a bidirectional distribution that closely approximates the product of the illumination and BRDF. Drawing visibility samples from this new distribution significantly reduces the sampling variance. As a main advance over previous work, our method allows for unstructured sources, including arbitrary local direct lighting and one-bounce of indirect lighting.

title: Precomputed Visibility Cuts for Interactive Relighting with Dynamic BRDFs
abstract: This paper presents a novel PRT-based method that uses precomputed visibility cuts for interactive relighting with all-frequency environment maps and arbitrary dynamic BRDFs. Our method is inspired by the recent Lightcuts approach  and we parameterize distant environment lighting onto uniformly distributed sample points over the sphere. Using a binary tree structure of the points, we precompute and approximate each vertex's visibility function into clusters that we call the precomputed visibility cuts. These cuts are iteratively selected with bounded approximation error and confined cluster size. At run-time, a GPU-based relighting algorithm quickly computes the view-dependent shading color by accessing a dynamically built light tree, the precomputed visibility cuts, and a direct sampling of an arbitrary BRDF using each visibility cluster's average direction and the dynamic view direction. Compared to existing PRT techniques, our method guarantees uniform sampling of the lighting, requires no precomputed BRDF data, and can be easily extended to handle one-bounce glossy indirect transfer effects in real-time.

title: Outdoor Face Recognition Using Enhanced Near Infrared Imaging
abstract: 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.

title: Fast, Sub-pixel Antialiased Shadow Maps
abstract: 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.

title: Real-time KD-tree construction on graphics hardware
abstract: We present an algorithm for constructing kd-trees on GPUs. This algorithm achieves real-time performance by exploiting the GPU's streaming architecture at all stages of kd-tree construction. Unlike previous parallel kd-tree algorithms, our method builds tree nodes completely in BFS (breadth-first search) order. We also develop a special strategy for large nodes at upper tree levels so as to further exploit the fine-grained parallelism of GPUs. For these nodes, we parallelize the computation over all geometric primitives instead of nodes at each level. Finally, in order to maintain kd-tree quality, we introduce novel schemes for fast evaluation of node split costs.
 As far as we know, ours is the first real-time kd-tree algorithm on the GPU. The kd-trees built by our algorithm are of comparable quality as those constructed by off-line CPU algorithms. In terms of speed, our algorithm is significantly faster than well-optimized single-core CPU algorithms and competitive with multi-core CPU algorithms. Our algorithm provides a general way for handling dynamic scenes on the GPU. We demonstrate the potential of our algorithm in applications involving dynamic scenes, including GPU ray tracing, interactive photon mapping, and point cloud modeling.

title: Using Recognizing Textual Entailment as a Core Engine for Answer Validation
abstract: This paper is about our approach to answer validation, which centered by a Recognizing Textual Entailment (RTE) core engine. We first combined the question and the answer into Hypothesis (H) and view the document as Text (T); then, we used our RTE system to check whether the entailment relation holds between them. Our system was evaluated on the Answer Validation Exercise (AVE) task and achieved f-measures of 0.46 and 0.55 for two submission runs, which both outperformed others' results for the English language.

title: Side-Channel Leaks in Web Applications: A Reality Today, a Challenge Tomorrow
abstract: With software-as-a-service becoming mainstream, more and more applications are delivered to the client through the Web. Unlike a desktop application, a web application is split into browser-side and server-side components. A subset of the application’s internal information flows are inevitably exposed on the network. We show that despite encryption, such a side-channel information leak is a realistic and serious threat to user privacy. Specifically, we found that surprisingly detailed sensitive information is being leaked out from a number of high-profile, top-of-the-line web applications in healthcare, taxation, investment and web search: an eavesdropper can infer the illnesses/medications/surgeries of the user, her family income and investment secrets, despite HTTPS protection; a stranger on the street can glean enterprise employees' web search queries, despite WPA/WPA2 Wi-Fi encryption. More importantly, the root causes of the problem are some fundamental characteristics of web applications: stateful communication, low entropy input for better interaction, and significant traffic distinctions. As a result, the scope of the problem seems industry-wide. We further present a concrete analysis to demonstrate the challenges of mitigating such a threat, which points to the necessity of a disciplined engineering practice for side-channel mitigations in future web application developments.