Fire, Flow and Flight

Summary: We present a novel method for the combustion of botanical tree models. Tree models are represented as particles that store biological and physical attributes that drive the kinetic behavior of a plant and the exothermic reaction of the combustion, which is efficiently processed in real-time.

Author(s): Soeren Pirk, Stanford Univeristy
Michał Jarząbek, Adam Mickiewicz University
Torsten Hädrich, King Abdullah University Of Science And Technology (KAUST)
Dominik L. Michels, King Abdullah University Of Science And Technology (KAUST)
Wojciech Palubicki, Adam Mickiewicz University

Speaker(s): Torsten Hädrich, King Abdullah University Of Science And Technology (KAUST)

Summary: We present a control method for flying creatures, which are aerodynamically simulated, interactively controllable, and equipped with a variety of motor skills such as soaring, gliding, hovering, and diving. Each motor skill is represented as Deep Neural Networks (DNN) and learned using Deep Q-Learning (DQL).

Author(s): Jungdam Won, Seoul National University
Jongho Park, Seoul National University
Kwanyu Kim, Seoul National University
Jehee Lee, Seoul National University

Speaker(s): Jungdam Won, Seoul National University

Summary: A reformation of soap film dynamics as a hyperbolic geometric flow. Our model provides a fast simulation that elegantly leads films to the steady states as Plateau's laws describe.

Author(s): Sadashige ISHIDA, The University of Tokyo, Nikon Corporation
Masafumi YAMAMOTO, The University of Tokyo
Ryoichi ANDO, National Institute of Informatics
Toshiya HACHISUKA, The University of Tokyo

Speaker(s): Sadashige Ishida, Nikon Corporation, and The University of Tokyo

Summary: This paper demonstrates a framework that enables city-scale traffic visualization and animation through statistical learning and metamodel-based optimization.

Author(s): Weizi Li, University of North Carolina at Chapel Hill
David Wolinski, University of North Carolina at Chapel Hill
Ming Lin, University of North Carolina at Chapel Hill

Speaker(s): Weizi Li, University of North Carolina at Chapel Hill