Guofu Xie

Diffusion curve textures for resolution independent texture mapping

We introduce a vector representation called diffusion curve textures for mapping diffusion curve images (DCI) onto arbitrary surfaces. In contrast to the original implicit representation of DCIs [Orzan et al. 2008], where determining a single texture value requires iterative computation of the entire DCI via the Poisson equation, diffusion curve textures provide an explicit representation from which the texture value at any point can be solved directly, while preserving the compactness and resolution independence of diffusion curves. This is achieved through a formulation of the DCI diffusion process in terms of Greens functions. This formulation furthermore allows the texture value of any rectangular region (e.g. pixel area) to be solved in closed form, which facilitates anti-aliasing. We develop a GPU algorithm that renders anti-aliased diffusion curve textures in real time, and demonstrate the effectiveness of this method through high quality renderings with detailed control curves and color variations.

Hierarchical diffusion curves for accurate automatic image vectorization

Diffusion curve primitives are a compact and powerful representation for vector images. While several vector image authoring tools leverage these representations, automatically and accurately vectorizing arbitrary raster images using diffusion curves remains a difficult problem. We automatically generate sparse diffusion curve vectorizations of raster images by fitting curves in the Laplacian domain. Our approach is fast, combines Laplacian and bilaplacian diffusion curve representations, and generates a hierarchical representation that accurately reconstructs both vector art and natural images. The key idea of our method is to trace curves in the Laplacian domain, which captures both sharp and smooth image features, across scales, more robustly than previous image- and gradient-domain fitting strategies. The sparse set of curves generated by our method accurately reconstructs images and often closely matches tediously hand-authored curve data. Also, our hierarchical curves are readily usable in all existing editing frameworks. We validate our method on a broad class of images, including natural images, synthesized images with turbulent multi-scale details, and traditional vector-art, as well as illustrating simple multi-scale abstraction and color editing results.

Line segment sampling with blue-noise properties

Line segment sampling has recently been adopted in many rendering algorithms for better handling of a wide range of effects such as motion blur, defocus blur and scattering media. A question naturally raised is how to generate line segment samples with good properties that can effectively reduce variance and aliasing artifacts observed in the rendering results. This paper studies this problem and presents a frequency analysis of line segment sampling. The analysis shows that the frequency content of a line segment sample is equivalent to the weighted frequency content of a point sample. The weight introduces anisotropy that smoothly changes among point samples, line segment samples and line samples according to the lengths of the samples. Line segment sampling thus makes it possible to achieve a balance between noise (point sampling) and aliasing (line sampling) under the same sampling rate. Based on the analysis, we propose a line segment sampling scheme to preserve blue-noise properties of samples which can significantly reduce noise and aliasing artifacts in reconstruction results. We demonstrate that our sampling scheme improves the quality of depth-of-field rendering, motion blur rendering, and temporal light field reconstruction.

Memory-Efficient Single-Pass GPU Rendering of Multifragment Effects

Rendering multifragment effects using graphics processing units (GPUs) is attractive for high speed. However, the efficiency is seriously compromised, because ordering fragments on GPUs is not easy and the GPUs memory may not be large enough to store the whole scene geometry. Hitherto, existing methods have been unsuitable for large models or have required many passes for data transmission from CPU to GPU, resulting in a bottleneck for speedup. This paper presents a stream method for accurate rendering of multifragment effects. It decomposes the model into parts and manages these in an efficient manner, guaranteeing that the parts can easily be ordered with respect to any viewpoint, and that each part can be rendered correctly on the GPU. Thus, we can transmit the model data part by part, and once a part has been loaded onto the GPU, we immediately render it and composite its result with the results of the processed parts. In this way, we need only a single pass for data access with a very low bounded memory requirement. Moreover, we treat parts in packs for further acceleration. Results show that our method is much faster than existing methods and can easily handle large models of any size.

Integrating Clipped Spherical Harmonics Expansions

Many applications in rendering rely on integrating functions over spherical polygons. We present a new numerical solution for computing the integral of spherical harmonics (SH) expansions clipped to polygonal domains. Our solution, based on zonal decompositions of spherical integrands and discrete contour integration, introduces an important numerical operating for SH expansions in rendering applications. Our method is simple, efficient, and scales linearly in the bandlimited integrand’s harmonic expansion. We apply our technique to problems in rendering, including surface and volume shading, hierarchical product importance sampling, and fast basis projection for interactive rendering. Moreover, we show how to handle general, nonpolynomial integrands in a Monte Carlo setting using control variates. Our technique computes the integral of bandlimited spherical functions with performance competitive to (or faster than) more general numerical integration methods for a broad class of problems, both in offline and interactive rendering contexts. Our implementation is simple, relying only on self-contained SH evaluation and discrete contour integration routines, and we release a full source CPU-only and shader-based implementations (<750 lines of commented code).

Interactive Depth-of-Field Rendering with Secondary Rays

This paper presents an efficient method to trace secondary rays in depth-of-field (DOF) rendering, which significantly enhances realism. Till now, the effects by secondary rays have been little addressed in real-time/interactive DOF rendering, because secondary rays have less coherence than primary rays, making them very difficult to handle. We propose novel measures to cluster secondary rays, and take a virtual viewpoint to construct a layered image-based representation for the objects that would be intersected by a cluster of secondary rays respectively. Therefore, we can exploit coherence of secondary rays in the clusters to speed up tracing secondary rays in DOF rendering. Results show that we can interactively achieve DOF rendering effects with reflections or refractions on a commodity graphics card.

Efficient search of lightcuts by spatial clustering

Lightcuts is an efficient illumination method for scenes with many complex lights, by hierarchical clustering of lights in a light tree. However, when the light tree is large, it is very time-consuming to traverse in the tree to get the suitable clusters of lights for illumination computation. For this, some methods proposed to use image coherence for neighboring pixels to share clusters of lights, and so save traversal cost in the light tree. However, with the image resolutions reduced, fewer and fewer coherences could be used and so their acceleration efficiency will be reduced dramatically, and they may even decrease the rendering efficiency. This sketch proposes to exploit spatial coherences to enhance rendering by lightcuts. For the intersection points between rays and the scene, they are clustered on the fly and the points of a cluster search their respective suitable clusters of lights from a common set of clusters, called a common cut. In this way, the traversal cost from the tree root to the common cuts can be considerably saved for acceleration. Results show that our method can be faster than the methods using image coherence, and works stably with various image resolutions. And with the lights being more complex, our method can obtain more acceleration.