Affiliation:
1. HACETTEPE UNIVERSITY
2. HACETTEPE ÜNİVERSİTESİ
Abstract
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 LRI coordinates and the dimensions covering 95% of the data are automatically selected using PCA. 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 show that 45% of the participants preferred the keyframes extracted using the proposed method, outperforming the alternative by 6%.
Publisher
Sakarya University Journal of Science