AdaSplats: Adaptive Splatting of Point Clouds for Accurate 3D Modeling and Real-time High-Fidelity LiDAR Simulation

LiDAR sensors provide rich 3D information about their surrounding and are becoming increasingly important for autonomous vehicles tasks, such as semantic segmentation, object detection, and tracking. Simulating a LiDAR sensor accelerates the testing, validation, and deployment of autonomous vehicles, while reducing the cost and eliminating the risks of testing in real-world scenarios. We address the problem of high-fidelity LiDAR simulation and present a pipeline that leverages real-world point clouds acquired by mobile mapping systems. Point-based geometry representations, more specifically splats, have proven their ability to accurately model the underlying surface in very large point clouds. We introduce an adaptive splats generation method that accurately models the underlying 3D geometry, especially for thin structures. Moreover, we introduce a physics-based, faster-than-real-time LiDAR simulator, in the splatted model, leveraging the GPU parallel architecture with an acceleration structure, while focusing on efficiently handling large point clouds. We test our LiDAR simulation in real-world conditions, showing qualitative and quantitative results compared to basic splatting and meshing techniques, demonstrating the interest of our modeling technique.Comment: 28 pages, 11 figures, 6 table

Evaluating the Performance of Vulkan GLSL Compute Shaders in Real-Time Ray-Traced Audio Propagation Through 3D Virtual Environments

Real time ray tracing is a growing area of interest with applications in audio processing. However, real time audio processing comes with strict performance requirements, which parallel computing is often used to overcome. As graphics processing units (GPUs) have become more powerful and programmable, general-purpose computing on graphics processing units (GPGPU) has allowed GPUs to become extremely powerful parallel processors, leading them to become more prevalent in the domain of audio processing through platforms such as CUDA. The aim of this research was to investigate the potential of GLSL compute shaders in the domain of real time audio processing. Specifically regarding real time ray tracing tasks. To do this a number of GLSL compute shaders were created, along with a C++ Vulkan application with which to execute them. These shaders facilitate the propagation of audio, using ray tracing, through a virtual environment, and implement 3D space partitioning and ray intersection prediction in order to gauge the effectiveness of these optimisations for this task. Statistically significant results show that the GLSL compute shaders successfully propagated audio through a virtual environment, returning results to the host system in real time, within 30 milliseconds. However, while this capability was shown, significantly detailed virtual environments prevented results from being returned in real time. Indicating a potential for future research and optimisation