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Simulating virtual crowds with 100,000 agents in realtime

When: 11:00AM - 12:00PM , March 19, 2018

Where: S-3-143

Speaker: Tomer Weiss


The In recent years, computer graphics researchers have proposed position-based methods for various simulation and animation purposes. These methods have become increasingly popular due to their simple, yet powerful and efficient simulation outcomes. In this talk, I focus on my recent work in developing a position-based framework for novel simulation and modeling for graphics applications. I demonstrate the framework's strengths by simulating large crowd masses in interactive rates for hundreds of thousands of agents, which was previously unachievable. Agent’s are simulated as particles, with short-range and long-range collision avoidance constraints to simulate both sparse and dense crowds. These positional constraints can be readily integrated into a standard PBD solver. This new method is suitable for use in interactive games, and was recently presented in the ACM SIGGRAPH conference on Motion in Games 2017, where it received the best paper award.

I conclude by presenting my work in interior layouts synthesis. A common approach for modeling researchers it to view interior layout synthesis as a mathematical optimization problem. Due to the complex nature of these problems, recent work employed a probabilistic scheme to effectively sample viable layout candidates, which is inefficient for large numbers of objects. I present recent results demonstrate that a PBD-driven layout synthesis, which is faster by an order of magnitude than the state-of-the-art, enabling quick prototyping of large-scale layouts that were previously intractable.

Speaker Bio

Tomer Weiss is a PhD candidate at the University of California Los Angeles, scheduled to defend this thesis in this year. He received the best paper award from the ACM SIGGRAPH conference on motion in games, for his work on virtual crowd simulation. He received his BSc degree in computer science from Tel Aviv University in 2013, and MS in Computer Science from UCLA in 2016. His research interests include computer graphics and optimization methods. He is a member of the UCLA Computer Graphics & Vision Laboratory, directed by Professor Demetri Terzopoulos

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