Precomputed Visibility Cuts for Interactive Relighting with Dynamic BRDFs
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: 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: All-frequency relighting of glossy objects
abstract: We present a technique for interactive rendering of glossy objects in complex and dynamic lighting environments that captures interreflections and all-frequency shadows. Our system is based on precomputed radiance transfer and separable BRDF approximation. We factor glossy BRDFs using a separable decomposition and keep only a few low-order approximation terms, each consisting of a purely view-dependent and a purely light-dependent component. In the precomputation step, for every vertex, we sample its visibility and compute a direct illumination transport vector corresponding to each BRDF term. We use modern graphics hardware to accelerate this step and further compress the data using a nonlinear wavelet approximation. The direct illumination pass is followed by one or more interreflection passes, each of which gathers compressed transport vectors from the previous pass to produce global illumination transport vectors. To render at run time, we dynamically sample the lighting to produce a light vector, also represented in a wavelet basis. We compute the inner product of the light vector with the precomputed transport vectors, and the results are further combined with the BRDF view-dependent components to produce vertex colors. We describe acceleration of the rendering algorithm using programmable graphics hardware and discuss the limitations and trade-offs imposed by the hardware.

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: An efficient GPU-based approach for interactive global illumination
abstract: This paper presents a GPU-based method for interactive global illumination that integrates complex effects such as multi-bounce indirect lighting, glossy reflections, caustics, and arbitrary specular paths. Our method builds upon scattered data sampling and interpolation on the GPU. We start with raytraced shading points and partition them into coherent shading clusters using adaptive seeding followed by k-means. At each cluster center we apply final gather to evaluate its incident irradiance using GPU-based photon mapping. We approximate the entire photon tree as a compact illumination cut, thus reducing the final gather cost for each ray. The sampled irradiance values are then interpolated at all shading points to produce rendering. Our method exploits the spatial coherence of illumination to reduce sampling cost. We sample sparsely and the distribution of sample points conforms with the underlying illumination changes. Therefore our method is both fast and preserves high rendering quality. Although the same property has been exploited by previous caching and adaptive sampling methods, these methods typically require sequential computation of sample points, making them ill-suited for the GPU. In contrast, we select sample points adaptively in a single pass, enabling parallel computation. As a result, our algorithm runs entirely on the GPU, achieving interactive rates for scenes with complex illumination effects.

title: Inference Rules and their Application to Recognizing Textual Entailment
abstract: In this paper, we explore ways of improving an inference rule collection and its application to the task of recognizing textual entailment. For this purpose, we start with an automatically acquired collection and we propose methods to refine it and obtain more rules using a hand-crafted lexical resource. Following this, we derive a dependency-based structure representation from texts, which aims to provide a proper base for the inference rule application. The evaluation of our approach on the recognizing textual entailment data shows promising results on precision and the error analysis suggests possible improvements.

title: Panalyst: Privacy-Aware Remote Error Analysis on Commodity Software
abstract: Remote error analysis aims at timely detection and remedy of software vulnerabilities through analyzing run-time errors that occur on the client. This objective can only be achieved by offering users effective protection of their private information and minimizing the performance impact of the analysis on their systems without undermining the amount of information the server can access for understanding errors. To this end, we propose in the paper a new technique for privacy-aware remote analysis, called Panalyst. Panalyst includes a client component and a server component. Once a runtime exception happens to an application, Panalyst client sends the server an initial error report that includes only public information regarding the error, such as the length of the packet that triggers the exception. Using an input built from the report, Panalyst server performs a taint analysis and symbolic execution on the application, and adjusts the input by querying the client about the information upon which the execution of the application depends. The client agrees to answer only when the reply does not give away too much user information. In this way, an input that reproduces the error can be gradually built on the server under the client's consent. Our experimental study of this technique demonstrates that it exposes a very small amount of user information, introduces negligible overheads to the client and enables the server to effectively analyze an error.

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: Decentralized Fair Resource Allocation for Relay-Assisted Cognitive Cellular Downlink Systems
abstract: In this paper, we consider a relay-assisted cognitive cellular downlink system dynamically accessing a spectrum licensed to a primary network, thereby improving the efficiency of spectrum usage. A cluster-based relay-assisted architecture is proposed, where relay stations are employed for minimizing the interference to users in the primary network and achieving fairness for cell-edge users. Based on this architecture, an optimal solution is derived for jointly controlling data rate, transmission power, and subband allocation to optimize the weighted sum goodput where proportional fair scheduling (PFS) is included as a special case. As shown by simulations, the proposed solution achieves significant throughput gains and better user fairness compared with existing designs.