| Research Goals | "In this video we will apply existing animation techniques to the special case of animating the dead..." |
| Principles | |
| Experiments | Keyframe
Kinematics Forward/Inverse Dynamics Forward/Inverse Motion Capture Optical/Magnetic Muybridge - reduced to 1 camera For each we have a general case with four sections
|
| Conclusions | Highly Compressable |
| Future Work | Modeling
Rendering Cloth Animation |
| References | |
| Key Phrases | Killer App
Body of Research Re-animating the dead Decay over time Skeletal Animation Dead reckoning |
| Title | Timing | Point | Visual | Sound | |
| Introduction | 10 sec | Researcher talking with monitor flickering in background, lots of fuzz
in the sound
"In this video..." |
|||
| Optical Motion Capture | 10 sec | Muybridge - reduced to 1 camera | Old stock video of Running Man, new footage of body on floor. | ||
| Magnetic Motion Capture | 3 sec | One motion capture of dead generalizes to others | Dead body dressed in diving suit, picture of morgue door | ||
| Forward Dynamics | We can get exact equation for the dead | ||||
| Conclusion | 5 sec | Highly Compressable | |||
| References | 3 sec | References |
Acme
Anvil
O O
/A\ /B\
,/ \, ,/ \,
Therefore...
O
/A\
,/ \, ,_,/\_/x
(note: I can get actual equations when the character exists.)
/ ! \
| % |
| $ | => some other goblegook
| # |
| @ |
\ * /
this is easily seen to be:
/ ! 4 f 3 f s v b 3 4 2 1 \
| % h w [ p 3 n m 5 w 8 q |
| $ 0 f w 4 5 g q b y z g |
| # t 5 f w m v g a g g l |
| @ f a s 3 h 6 4 n c v z |
\ * w 4 z g f 0 s v n c r /
And this is
A^-1 x Q
where Q is the orientation matrix
We solve for w first and get a relation for z g and a
which we solve by assigning a negative energy to rotations
and finding the minimum enegry system in m dimenstions
using numerical methods.
Each constraint may be solved in parallel so we used a
consumer IBM SP2 computer running Java 1.1.6 to solve
these equations in real-time.
In human models there generally exist multiple solutions due
to redundant degrees of freedom. In animating the dead, the
degrees of freedom decay over time. At the limit, in the post-rigur
model, we can eliminate joint rotations from matrix A
A=I
This is a very smart development, as our production
Inverse Kinematics solver finds a unique solution
in near real-time on a Palm IIIe running
Java 1.2.2.
4
/A>
/\
\ \
*----------------------*
,_,/\_/x
*----------------------*
pan right to left
from Gearga Tech We have developed a simulation of a human diver with 38 controlled degrees of freedom. The human model can perform a number of 10 meter platform dives. The dynamic model of the diver consists of 15 rigid bodies connected by rotary joints. The dynamic properties of the rigid bodies were calculated using densities for each body part measured from cadavers[2], and algorithms for computing moments of inertia from polygonal objects[5]. The equations of motion were generated using a commercially available package, that uses a variant of Kane's method with a symbolic simplification phase[8].We have also tackled the problem of the dynamics of the dead.
(repeat like egg breaking video with live actor falling at the end of each simulation)
O
/A\
,/ \,
------------
<--------> shake platform, observe dynamic simulation
,_,/\_/x
------------
<--------> shake platform, observe dynamic simulation
/ /
/ /
O(_/
/A\
,/ \,
------------ finger from heaven, using haptic interface to squash subject
/ /
/ /
(_/
,_,/\_/x
------------ finger from heaven, using haptic interface to squash subject
We will now repeat this experiment
Acme
Anvil
O O
/C\ /A\
,/ \, ,/ \,
Others... Adjusting Walk Cycles for different subjects (Georgia Tech Work.)
Zhao, Jianmin An articulated figure is often modeled as a set of rigid segments connected with joints. Its configuration can be altered by varying the joint angles. Although it is straight forward to compute figure configurations given joint angles (forward kinematics), it is more difficult to find the joint angles for a desired configuration (inverse kinematics). Since the inverse kinematics problem is of special importance to an animator wishing to set a figure to a posture satisfying a set of positioning constraints, researchers have proposed several different approaches. However, when we try to follow these approaches in an interactive animation system where the object on which to operate is as highly articulated as a realistic human figure, they fail in either generality or performance. So, we approach this problem through nonlinear programming techniques. It has been successfully used since 1988 in the spatial constraint system within Jack, a human figure simulation system developed at the University of Pennsylvania, and proves to be satisfactorily efficient, controllable, and robust. A spatial constraint in our system involves two parts: one constraint on the figure, the end-effector, and one on the spatial environment, the goal. These two parts are dealt with separately, so that we can achieve a neat modular implementation. Constraints can be added one at a time with appropriate weights designating the importance of this constraint relative to the others and are always solved as a group. If physical limits prevent satisfaction of all the constraints, the system stops with the (possibly local) optimal solution for the given weights. Also, the rigidity of each joint angle can be controlled, which is useful for redundant degrees of freedom.
Badler, Norman I.
ACM Transactions on Graphics
Vol.13, No. 4 (Oct. 1994), pp. 313-336
Abstract