Keyframe Extraction Using Linear Rotation Invariant Coordinates

Keyframe extraction is a widely applied remedy for issues faced with 3D motion capture -based computer animation. In this paper, we propose a novel keyframe extraction method, where the motion is represented in linear rotation invariant coordinates and the dimensions covering 95% of the data are automatically selected using principal component analysis. Then, by K-means classification, the summarized data is clustered and a keyframe is extracted from each cluster based on cosine similarity. To validate the method, an online user study was conducted. The results of the user study show that 45% of the participants preferred the keyframes extracted using the proposed method, outperforming the alternative by 6%.

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