Two Minute Papers – Simulating Breaking Glass

Time to smash virtual objects in slow motion! There is something inherently exciting about watching breaking glass and other objects. Researchers in computer graphics also like to have some fun and write simulation programs to smash together a variety of virtual objects in slow motion. However, despite being beautiful, they are physically not correct as many effects are neglected, such as simulating plasticity, bending stiffness, stretching energies and many others. Pfaff et al.’s paper “Adaptive Tearing and Cracking of Thin Sheets” addresses this issue by creating an adaptive simulator that uses more computational resources only around regions where cracks are likely to happen.

This new technique enables the simulation of tearing for a variety of materials like cork, foils, metals, vinyl and it also yields physically correct results for glass. The algorithm also lets artists influence the outcome to be in line with their artistic visions.

Pfaff et al.’s research paper “Adaptive Tearing and Cracking of Thin Sheets” is available here.

Two Minute Papers – Artificial Neural Networks and Deep Learning

Artificial neural networks and deep learning provide us incredibly powerful tools in machine learning that are useful for a variety of tasks ranging from image classification to voice translation. So what is all the deep learning rage about? The media seems to be all over the newest neural network research of the DeepMind company that was recently acquired by Google. They used neural networks to create algorithms that are able to play Atari games, learn them like a human would, eventually achieving superhuman performance.

Deep learning means that we use artificial neural networks with multiple layers, making it even more powerful for more difficult tasks. These machine learning techniques proved to be useful for many tasks beyond image recognition: they also excel at weather predictions, breast cancer cell mitosis detection, brain image segmentation and toxicity prediction among many others. If you would like to know more about neural networks and deep learning, make sure to check out this talk from Andrew Ng.

In Two Minute Papers, I attempt to bring the most awesome research discoveries to everyone a couple minutes at a time.


Two Minute Papers – Capturing Waves of Light With Femto-photography

Researchers at MIT and the University of Zaragoza used a technique called femto-photography to capture how a waves of light propagate in space and time. Awesome, isn’t it? 🙂

What is femto-photography? To be able to capture how waves of light propagate in space, one would need to build a camera that is able to take one trillion frames per second. At first, this sounds impossible, but researchers at MIT and the University of Zaragoza have managed to crack this nut: in their newest work they published to SIGGRAPH that they call femto-photography, we can observe how a mirror lights up with its image as light propagates from the light source to the camera. All this in slow motion!

Two Minute Papers – Creating Stunning Fluid Simulations with Wavelet Turbulence

A quick two minute explanation of one of the greatest fluid papers ever written: the Academy Award-winning Wavelet Turbulence.

Creating detailed fluid and smoke simulations in Blender and other modeling software is a slow and laborious process that requires a ton of time and resources. Wavelet Turbulence is a technique that helps achieving similar effects orders of magnitude faster. It is also much lighter on memory and is now widely used in the industry, so it’s definitely not an accident that Theodore Kim won an Academy Award (a technical Oscar, if you will) for this SIGGRAPH publication. It is implemented in Blender and is available for everyone free of charge, so make sure to try it out! The paper is available here.