Indirect illumination is an important element for realistic image synthesis, but its computation is expensive and highly dependent on the complexity of the scene and of the BRDF of the surfaces involved. While off-line computation and pre-baking can be acceptable for some cases, many applications (games, simulators, etc.) require real-time or interactive approaches to evaluate indirect illumination. In this paper, we present a novel real-time solution that calculates two light bounces - either glossy or diffuse - using a hierarchical voxel representation generated from a regular scene mesh. Our algorithm consists of two steps. First, direct illumination information (energy and direction) is emitted from dynamic area light sources and splatted into the voxel hierarchy, accounting for possible occluders. Secondly, we draw the scene mesh and compute the illumination in the pixel shader by combining the direct illumination and the indirect illumination received from the rest of the scene. For the latter, our approach employs an approximate voxel cone tracing to efficiently collect visibility and light in the hierarchical voxel representation of the scene. Our solution offers real-time and almost geometry-independent performance with a high visual quality for complex scenes with diffuse, as well as glossy surfaces.

Abstract Indirect illumination is an important element for realistic image synthesis, but its computation is expensive and highly dependent on the complexity of the scene and of the BRDF of the involved surfaces. While off‐line computation and pre‐baking can be acceptable for some cases, many applications (games, simulators, etc.) require real‐time or interactive approaches to evaluate indirect illumination. We present a novel algorithm to compute indirect lighting in real‐time that avoids costly precomputation steps and is not restricted to low‐frequency illumination. It is based on a hierarchical voxel octree representation generated and updated on the fly from a regular scene mesh coupled with an approximate voxel cone tracing that allows for a fast estimation of the visibility and incoming energy. Our approach can manage two light bounces for both Lambertian and glossy materials at interactive framerates (25–70FPS). It exhibits an almost scene‐independent performance and can handle complex scenes with dynamic content thanks to an interactive octree‐voxelization scheme. In addition, we demonstrate that our voxel cone tracing can be used to efficiently estimate Ambient Occlusion.

We present an approach for rendering the surface of a particle-based fluid that is simple to implement, has real-time performance with a configurable speed/quality trade-off, and smoothes the surface to prevent the fluid from looking "blobby" or jelly-like. The method is not based on polygonization and as such circumvents the usual grid artifacts of marching cubes. It only renders the surface where it is visible, and has inherent view-dependent level-of-detail. We use Perlin noise to add detail to the surface of the fluid. All the processing, rendering and shading steps are directly implemented on graphics hardware.

In this paper, we present Confetti, a novel point-based rendering approach based on object-space point interpolation of densely sampled surfaces. We introduce the concept of a transformation-invariant covariance matrix of a set of points which can efficiently be used to determine splat sizes in a multiresolution point hierarchy. We also analyze continuous point interpolation in object-space and we define a new class of parameterized blending kernels as well as a normalization procedure to achieve smooth blending. Furthermore, we present a hardware accelerated rendering algorithm based on texture mapping and alpha-blending as well as programmable vertex and pixel-shaders.

Camera calibration is a critical problem in applications such as augmented reality and image based model reconstruction. When constructing a 3D model of an object from an uncalibrated video sequence, large amounts of frames and self occlusions of parts of the object are common and difficult problems. In this paper we present a fast and robust algorithm that uses a divide and conquer strategy to split the video sequence into sub-sequences containing only the most relevant frames. Then a robust stratified linear based algorithm is able to calibrate each of the subsequences to a metric structure and finally the subsequences are merged together and a final nonlinear optimization refines the solution. Examples of real data reconstructions are presented.

We present a novel point-based rendering approach based on object-space point interpolation. We introduce the concept of a transformation-invariant covariance matrix of a set of points to efficiently determine splat sizes in a multiresolution hierarchy. We analyze continuous point interpolation in object-space, and define a new class of parametrized blending kernels to achieve smooth blending. Furthermore, we present a hardware accelerated rendering algorithm based on α-texture mapping and α-blending.

Automatic generation of models from a set of positive and negative samples and a-priori knowledge (if available) is a crucial issue for pattern recognition applications. Grammatical inference can play an important role in this issue since it can be used to generate the set of model classes, where each class consists on the rules to generate the models. In this paper we present the process of learning context dependent bidimensional objects from outdoors images as context sensitive languages. We show how the process is conceived to overcome the problem of generalizing rules based on a set of samples which have small differences due to noisy pixels. The learned models can be used to identify objects in outdoors images irrespectively of their size and partial occlusions. Some results of the inference procedure are shown in the paper.