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Abstract
We present in this paper a framework that generates free fall motions
for the object within a still fluid. We introduce a new motion
synthesis approach where six characteristic motion prototypes of
free fall are defined and synthesized, and then the motion trajectory
is specified form free fall motion graph. We automatically create
motion sequences using trajectory search tree and pre-computed
trajectory database. The proposed approach can produce realistic
and controllable free fall motion that could be applied in many different
applications, including virtual reality, game and other entertainment
productions.
CR Categories: I.2.7 [Articial Intelligence]: Problem Solving,
Control Methods and Search—Graph and tree search strategies;
I.3.7 [Computer Graphics]: Three-Dimensional Graphics and
Realism—Animation;
Keywords: physically based animation, motion prototypes, free
fall
1 Introduction
It is difficult to simulate the common and spectacular free falling
motions around us in computer graphics (e.g., paper, leaves, and
snowflakes within air). Our main purpose is to extract the physical
rules behind the phenomena and archive realistic simulation results.
Most motion generations of free fall are example-based approaches.
They synthesized the motion trajectories from captured video, simple
fluid simulation, commercial 3D animation software, or sketch
example. All these approaches ignored the nature of free fall and
considered the free fall as complex and unpredictable process using
complete stochastic model or simple particle representation in flow.
As the another approach, physicist recently focused on the unsteady
dynamic of free falling through thousands of experiments and this
remains a significant challenge [Razavi 2010].
In this work, we propose new approach combining both experimental
and theoretical results. About the free fall in computer graphics,
our primary focus examines all the motion types of light-weight
objects to create reliable and natural motion paths by using motion
planning in real time environment.
2 Motion Generation
Our method (Figure 1) uses the initial conditions and physical parameters
of a light-weight object with 6 degree of freedoms as inputs,
including the physical characteristics of the object and fluid
wherein released (release height, mass, etc.). We transform the parameters
to two important non-dimensional numbers Re and I,
and then lookup the phase diagram (Figure 1) of free fall to query
the main motion prototype which is the stable status for the falling
object.
After the main motion prototype is decided, we first determine the
motion types based on motion groups. For all motion types of the
decided motion type, our probability model is adopted to choose
the actual motion paths. In our work, the motion trajectory is constructed
from six motion sequences of motion prototypes. The free
fall motion graphs are used to synthesize the trajectories from the
designated motion segments. The final free fall motions are synthesized
after the initial trajectories are determined through optimization. |
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