Jacopo Pantaleoni

Learn More
A recently developed algorithm called Hierachical Linear Bounding Volume Hierarchies (HLBVH) has demonstrated the feasibility of reconstructing the spatial index needed for ray tracing in real-time, even in the presence of millions of fully dynamic triangles. In this work we present a simpler and faster variant of HLBVH, where all the complex book-keeping(More)
We present HLBVH and SAH-optimized HLBVH, two high performance BVH construction algorithms targeting real-time ray tracing of dynamic geometry. HLBVH provides a novel hierarchical formulation of the LBVH algorithm [LGS*09] and SAH-optimized HLBVH uses a new combination of HLBVH and the greedy surface area heuristic algorithm. These algorithms minimize work(More)
We present a highly flexible and efficient software pipeline for programmable triangle voxelization. The pipeline, entirely written in CUDA, supports both fully conservative and thin voxelizations, multiple boolean, floating point, vector-typed render targets, user-defined vertex and fragment shaders, and a bucketing mode which can be used to generate 3D(More)
We present a new sampling space for light transport paths that makes it possible to describe Monte Carlo path integration and photon density estimation in the same framework. A key contribution of our paper is the introduction of vertex perturbations, which extends the space of paths with loosely coupled connections. The new framework enables the(More)
We describe the architecture of a novel system for precomputing sparse directional occlusion caches. These caches are used for accelerating a fast cinematic lighting pipeline that works in the spherical harmonics domain. The system was used as a primary lighting technology in the movie Avatar, and is able to efficiently handle massive scenes of(More)
In this manuscript, inspired by a simpler reformulation of primary sample space Metropolis light transport, we derive a novel family of general Markov chain Monte Carlo algorithms called <i>charted Metropolis-Hastings</i>, that introduces the notion of <i>sampling charts</i> to extend a given sampling domain and make it easier to sample the desired target(More)
We first summarize the path integral formulation by Veach [Veach 1998]. Using the path integral formulation, light transport simulation can be expressed as: Ij = Ω fj (¯ x)dµ(¯ x), (1) where j is an index to the pixel (or measurement), fj is the measurement contribution function, µ is a measure of paths, and Ω is the set of transport paths of all lengths.(More)
  • 1