Markov-Type Vector Field for endless surface animation of water stream

Abstract

In this paper, we propose a hybrid (physical-stochastic) model of surface element (surfel) fluctuations for the visual simulation of an endlessly running water surface. This model comprises two main phases: preprocessing and endless animation phases. First, we simulate a physics-based method for a specific period of time during the preprocessing phase. We construct a stochastic vector field in the simulation, referred to as a Markov-Type Vector Field (MTVF), using only the surface values of the fluid flow. Next, we import the MTVF data into the main endless animation phase and create a surface fluctuation animation by surfels and temporary velocity field modeling of the MTVF using a random sample. In our approach, the surfel edges that cover the fluid flow domain are transferred simply via a temporary single velocity and the new flow surface is determined directly based on their positions. MTVF allows us to generate a water surface animation endlessly in real time without the time-consuming processes of solving the corresponding physical equations. We describe the MTVF construction method and the endless surface animation steps, as well as present the results of experiments that demonstrate the plausibility of our method.