MSc CAVE Project

Procedural modelling in Houdini based on Function Representation

Real Time Simulation of Game Character Clothing

Audio driven games

Procedural Forest Generation with L-System Instancing

Eulerian Smoke Simulation

Fluid Simulation using Smoothed Particle Hydrodynamics

An Investigation into an Assortment of Flocking Algorithms

Crowd Simulation based on Emergent Behaviours

Procedural generation of Bridges and Tunnels

Multiplexed Metropolis Light Transport

HDRI and Image Based Lighting

A Simple Pipeline for Denoising Renders with Neural Networks

3D Langrangian Fluid Solver using SPH approximations.

Genetically Evolved Motion Controllers

A User Friendly Hair Reflectance Model in Houdini

Fire Simulation System

Implementing a simple raytracer

Prototyping a Custom 3D Printing Slicer

Walking Penguin Crowd Simulation

Automatic rigging Tool for centipedes and millipedes

Procedural destruction in Houdini

Path Planning for Natural Phenomena

Thesis Simulating Snow with the Material Point Method Abstract This thesis discusses the research and development steps for the simulation of snow with the Material Point Method (MPM). In order to gain an understanding in the technique and mathematics the MPM was researched in detail.

OpenGL GPU Features and Fluid SPH

Implicit Skinning

Implicit Skinning

Wave Simulation

Cel-Shading with OSL in RenderMan21 for Maya

Crowd Simulation with Massive

Towards Realistic Hair Animation Using Discrete Elastic Rods

Pipeline Development for Winter Scenes and FX

Traversing Sparse Voxel Octrees

Swarm Intelligence simulating ant foraging behaviour

Soft Body Deformation Dynamics Based on Shape Matching

Wii Game

Melting Simulation with the Material Point Method

Robust Point Membership For Polygonal Meshes

Implementing Flame using a Mass Spring System

Beat Tracking to Control Lighting

Thesis Smooth Particle Hydrodynamics Abstract This paper discusses the implementation of a fluid solver which implements a version of Smooth Particle Hydrodynamics approximations using the prediction relaxation scheme proposed by Clavet et al.