Key frame extraction method of motion capture data

A key frame extraction method of motion capture data comprises the following steps: (1) feature representation; motion components including rotation angles of a trunk and limbs of a human body and a relative distance between joints of the body are used to represent main features of a human motion posture; (2) critical point screening; an extreme point and a dynamic and static conversion point of a motion component curve serve as a critical point, and a critical point reduction algorithm is used to select a key critical point; (3) key degree curve structure; selected key critical points are used to divide a motion component curve, so as to form a motion component key degree curve; (4) weight learning; and (5) key frame extraction; weighting and fitting are used for a motion component key degree curve of a target motion, and the key frame extraction is carried out based on a fitting curve. The invention does not need to manually set the hard-to-determine threshold, can learn different key frame extraction styles from the sample motion, and can extract the key frame according to several limb motions, so that the need for real-time processing of the motion capture data can be met.