Online Motion Retargetting
Online motion retargetting is a method to retarget the motion of a character to another in real-time.
The technique is based on inverse rate control, which computes the changes in joint
angles corresponding to the changes in end-effector position. While tracking the multiple end-effector
trajectories of the original subject or character, our on-line motion retargetting also minimizes the
joint angle differences by exploiting the kinematic redundancies of the animated model. This method
can generalize a captured motion for another anthropometry to perform slightly different motion, while
preserving the original motion characteristics. Because the above is done in on-line, a
real-time performance can be mapped to other characters. Moreover, if the method is used interactively
during motion capture session, the feedback of retargetted motion on the screen provides more chances to
get satisfactory results. As a by-product, our algorithm can be used to reduce measurement
errors in restoring captured motion. The data enhancement improves the accuracy in both joint
angles and end-effector positions. Experiments prove that our retargetting algorithm preserves the high
frequency details of the original motion quite accurately.
Schema
The input is a stream of joint angle vectors θd of the measured subject during the
source motion and another stream of the reference (or desired) end-effector positions
xd of the animated character at discrete time ticks. The output is a stream of joint angle
vectors θ of the animated character during the destination motion at corresponding time ticks.
The filter in the figure is causal. i.e., the output is calculated based on the current and
immediately previous input values, but does not dependent on the future input.
It explains why it is called on-line.
Example-1 : Walking motion
In this example, the source motion was curved path locomotion.
The walker took 13 steps along the path. The taller one in the snap
shots above is the source character. The same
foot trajectories were tracked by the smaller one mimicking the original motion.
Example-2 : Bat-swing motion
In this experiment, actual performance of a bat swing motion was processed by
our OMR to produce the destination motion of three different characters. Since the body
dimensions of Character B and the real performer are similar, the retargetted motion
doesn't contain any noticeable difference from the source motion. In the case
of Character A, however, we can see the waist is bent to lower the hit position, and the
torso is shifted forward to account for the shorter arms. In the case of Character
C, the torso is bent backward and makes a bigger twist to account for the longer arms
and shorter torso. Snap shots were taken during the retargetted motions to clearly demonstrate the
above adaptation for the anthropometric differences and shown in the above.
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Online Motion Retargetting
(PDF Format, 654 KB)
Proceedings of the International Pacific Graphics '99, Seoul Korea, October 5-7, 1999.
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