Efficient reconstruction of indoor scenes with color
We present an efficient and general approach to computing and integrating 3D distance fields directly from multiple range images. We compute normal and confidence values directly from a 2D range image. We then approximate 3D Euclidean distance by correcting the line-of-sight distance. To integrate multiple scans, we efficiently transform voxels of the target distance field to each scan's local coordinate system, then update voxels with computed distance and confidence values. Finally, we extract an iso-surface from the weighted distance field using the marching cubes algorithm. We extend the same idea to the assignment of weighted colors or texture coordinates to the reconstructed model. Experiments show that our approach is fast, has reasonable storage requirements, and can produce high-quality surfaces from multiple range scans.

title: Interactive Glossy Reflections using GPU-based Ray Tracing with Adaptive LOD
abstract: We present an interactive GPU-based algorithm for accurately rendering high-quality, dynamic glossy reflection effects from both HDR environment maps and local scene objects. Our method uses hardware rasterization to produce primary pixels, and GPU-based BRDF importance sampling [CK07] to quickly generate reflected rays. We utilize a fast GPU ray tracer proposed by Carr et al. [CHCH06] to compute reflection hits. Our main contribution is an adaptive level-of-detail (LOD) control algorithm that greatly improves ray tracing performance during reflection shading. Specifically, we use the solid angle represented by each reflected ray to adaptively pick the level of termination in the BVH traversal step during ray tracing. This leads to 2 ∼ 3x speedup over an unmodified implementation of [CHCH06]. Based on the same solid angle measure, we derive a texture filtering formula to reduce reflection aliasing artifacts, taking advantage of hardware MIP mapping. This extends the filtering algorithm presented in [CK07] from environment mapping to local scene reflection. Using our algorithm, we demonstrate interactive rendering rates for several scenes featuring dynamic lighting and material changes, spatially varying BRDF parameters, and rigid-body object movement.

title: Real-time editing and relighting of homogeneous translucent materials
abstract: Existing techniques for fast, high-quality rendering of translucent materials often fix BSSRDF parameters at precomputation time. We present a novel method for accurate rendering and relighting of translucent materials that also enables real-time editing and manipulation of homogeneous diffuse BSSRDFs. We first apply PCA analysis on diffuse multiple scattering to derive a compact basis set, consisting of only twelve 1D functions. We discovered that this small basis set is accurate enough to approximate a general diffuse scattering profile. For each basis, we then precompute light transport data representing the translucent transfer from a set of local illumination samples to each rendered vertex. This local transfer model allows our system to integrate a variety of lighting models in a single framework, including environment lighting, local area lights, and point lights. To reduce the PRT data size, we compress both the illumination and spatial dimensions using efficient nonlinear wavelets. To edit material properties in real-time, a user-defined diffuse BSSRDF is dynamically projected onto our precomputed basis set, and is then multiplied with the translucent transfer information on the fly. Using our system, we demonstrate realistic, real-time translucent material editing and relighting effects under a variety of complex, dynamic lighting scenarios.

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

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: Fast, realistic lighting and material design using nonlinear cut approximation
abstract: We present an efficient computational algorithm for functions represented by a nonlinear piecewise constant approximation called cuts. Our main contribution is a single traversal algorithm for merging cuts that allows for arbitrary pointwise computation, such as addition, multiplication, linear interpolation, and multi-product integration. A theoretical error bound of this approach can be proved using a statistical interpretation of cuts. Our algorithm extends naturally to computation with many cuts and maps easily to modern GPUs, leading to significant advantages over existing methods based on wavelet approximation. We apply this technique to the problem of realistic lighting and material design under complex illumination with arbitrary BRDFs. Our system smoothly integrates all-frequency relighting of shadows and reflections with dynamic per-pixel shading effects, such as bump mapping and spatially varying BRDFs. This combination of capabilities is typically missing in current systems. We represent illumination and precomputed visibility as nonlinear sparse vectors; we then use our cut merging algorithm to simultaneously interpolate visibility cuts at each pixel, and compute the triple product integral of the illumination, interpolated visibility, and dynamic BRDF samples. Finally, we present a two-pass, data-driven approach that exploits pilot visibility samples to optimize the construction of the light tree, leading to more efficient cuts and reduced datasets.

title: Motivated learning agent model for distributed collaborative systems
abstract: The paper develops and discusses a conceptual model for a Mixed Reality-based remote collaborative system (MR-Collab) based on motivated learning Agents. The proposed MR-Collab system is described in details as well to help better understand this model. Self-Development Agent based on previous work is an intelligent Agent, which not only receives information from sensors in the environment, but also gives valuable suggestions that could help to improve the system. The model is not limited to this specific system, but could be adapted to other collaboration systems as well.

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.

title: Real-time soft shadows in dynamic scenes using spherical harmonic exponentiation
abstract: Previous methods for soft shadows numerically integrate over many light directions at each receiver point, testing blocker visibility in each direction. We introduce a method for real-time soft shadows in dynamic scenes illuminated by large, low-frequency light sources where such integration is impractical. Our method operates on vectors representing low-frequency visibility of blockers in the spherical harmonic basis. Blocking geometry is modeled as a set of spheres; relatively few spheres capture the low-frequency blocking effect of complicated geometry. At each receiver point, we compute the product of visibility vectors for these blocker spheres as seen from the point. Instead of computing an expensive SH product per blocker as in previous work, we perform inexpensive vector sums to accumulate the log of blocker visibility. SH exponentiation then yields the product visibility vector over all blockers. We show how the SH exponentiation required can be approximated accurately and efficiently for low-order SH, accelerating previous CPU-based methods by a factor of 10 or more, depending on blocker complexity, and allowing real-time GPU implementation.

title: Bayesian Face Recognition Based on Markov Random Field Modeling
abstract: In this paper, a Bayesian method for face recognition is proposed based on Markov Random Fields (MRF) modeling. Constraints on image features as well as contextual relationships between them are explored and encoded into a cost function derived based on a statistical model of MRF. Gabor wavelet coefficients are used as the base features, and relationships between Gabor features at different pixel locations are used to provide higher order contextual constraints. The posterior probability of matching configuration is derived based on MRF modeling. Local search and discriminate analysis are used to evaluate local matches, and a contextual constraint is applied to evaluate mutual matches between local matches. The proposed MRF method provides a new perspective for modeling the face recognition problem. Experiments demonstrate promising results.

title: Precomputed Radiance Transfer Field for Rendering Interreflections in Dynamic Scenes
abstract: In this paper, we introduce a new representation – radiance transfer fields (RTF) – for rendering interreflections in dynamic scenes under low frequency illumination. The RTF describes the radiance transferred by an individual object to its surrounding space as a function of the incident radiance. An important property of RTF is its independence of the scene configuration, enabling interreflection computation in dynamic scenes. Secondly, RTFs naturally fit in with the rendering framework of precomputed shadow fields, incurring negligible cost to add interreflection effects. In addition, RTFs can be used to compute interreflections for both diffuse and glossy objects. We also show that RTF data can be highly compressed by clustered principal component analysis (CPCA), which not only reduces the memory cost but also accelerates rendering. Finally, we present some experimental results demonstrating our techniques.