Abstract
I
n showing human body motion , it is not difficult for computer graphics to show a motion with a designated meaning or to
show the motion of the meaning exaggeratedly. However, it is relatively difficult for computer graphics to show a daily
human body motion without any meaning in real life. The reason lies in the animation technology. The animation
technology adopts understandable motion or the special individuality that can identify the character to express the intention
of the character. However, when people are talking, there will be not only the motion and character expressions that are
understandable but also some daily motion with ambiguous intentions and meanings. It can assume that these motion s are
also necessary in showing human body motion by computer graphics. The study observed the human body motion during
the speech and classified these motions by each part of human bodies. The human body motion during the speech varied
based on their different body parts. The study carefully observed the hand motion and the motion of touching bodies in
particular. Among the motion , those unconscious, habitual motion , which didn’t reflect the meaning of the speech in
particular but often appeared in the communication, belong to the non meaning motion . After
con sulting the content of the
speech, the conducted research on the meaning of hand motion and found out that the initial motion is made to express the
content of the speech but the later motion have nothing to do with the speech and are just repeated motion similar to the
previous motion , like the motion of waving motion ””. Therefore, the later motion belongs to non meaning motion too. It is
worth mentioning that this kind of motion are in connection with upward, downward, left and right motion . These motions
are divided into 12 patterns based on their expressions in anatomy. In order to find out the actual motion , the study adopted
the measurement system to calculate the distances of the body motion during the speech through experiments, and
compared the distances of hand motion produced by each body parts. And the study took advantage of image processing to
obtain the tracks of hand motion , and decided to see the non meaning motion through the tracks.
