Real-time KD-tree construction on graphics hardware
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: Synthesizing trees by plantons
abstract: In this paper, we present a two-level statistical model for characterizing the stochastic and specific nature of trees. At the low level, we define plantons, which are a group of similar organs, to depict tree organ details statistically. At the high level, a set of transitions between plantons is provided to describe the stochastic distribution of organs.Based on such a tree model, we propose a novel tree modeling approach, synthesizing trees by plantons, which are extracted from tree samples. All tree samples are captured from the real world. We have designed a maximum likelihood estimation algorithm to acquire the two-level statistical tree model from single samples or multi- samples. Experimental results show that our new model is capable of synthesizing new trees with similar, yet visually different shapes.

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: Perceptually-motivated shape exaggeration
abstract: 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.

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.

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: 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: SketchML a representation language for novel sketch recognition approach
abstract: Multimodal interfaces can be profitably used to support increasingly complex services in assistive environments. In particular, sketch-based interfaces offer users an effortless and powerful communication way to represent concepts and commands on different devices. Unlike other modalities, sketch-based interaction can be easily fitted according to heterogeneous services. Moreover it can be quickly personalized according to the user needs.
 Developing a sketch-based interface for a specific service is a time-consuming operation that requires the re-engineering and/or the re-designing of the whole recognizer framework. This paper describes a definitive framework by which the user, simply by using freehand drawing, can define every kind of sketch-based interface. The definition of the interface and its recognition process are performed by using our developed Sketch Modeling Language (SketchML).

title: On the hardness of minimizing space for all-shortest-path interval routing schemes
abstract: k-Interval Routing Scheme (k-IRS) is a compact routing method that allows up to k interval labels to be assigned to an arc; and global k-IRS allows not more than a total of k interval labels in the whole network. A fundamental problem is to characterize the networks that admit k-IRS (or global k-IRS). Many of the problems related to single-shortest-path k-IRS have already been shown to be NP-complete. For all-shortest-path k-IRS, the characterization problem remains open for k>=1. In this paper, we study the time complexity of devising minimal-space all-shortest-path k-IRSs and show that it is NP-complete to decide whether a graph admits an all-shortest-path k-IRS, for every integer k>=3, and so is that of deciding whether a graph admits an all-shortest-path k-strict IRS, for every integer k>=4. These are the first NP-completeness results for all-shortest-path k-IRS where k is a constant and the graph is unweighted. The NP-completeness holds also for the linear case. We also prove that it is NP-complete to decide whether an unweighted graph admits an all-shortest-path IRS with global compactness of at most k, which also holds for the linear and strict cases.

title: Context-Centric Needs Anticipation Using Information Needs Graphs
abstract: Effective agent teamwork requires information exchange to be conducted in a proactive, selective, and intelligent way. In the field of distributed artificial intelligence, there has been increasing number of research focusing on need-driven proactive communication, both theoretically and practically. Among these works, CAST has realized a team-oriented agent architecture where agents, based on a computational shared mental model, are able to anticipate teammates' information needs and proactively deliver relevant information to the needers in a timely manner. However, the first implementation of CAST takes little consideration of the dynamics of the anticipated information needs, which can change in various ways as the context develops. In this paper we describe a novel mechanism for organizing and managing the “context” of information needs. This allows agents to dynamically activate and deactivate information needs progressively. It has been shown that the two-level context-centric approach can enhance team performance considerably.

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.