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%.
Keyframe extraction linear rotation invariant coordinates motion data summarization
Birincil Dil | İngilizce |
---|---|
Konular | Matematik |
Bölüm | Araştırma Makalesi |
Yazarlar | |
Yayımlanma Tarihi | 20 Ekim 2022 |
Gönderilme Tarihi | 25 Temmuz 2022 |
Kabul Tarihi | 5 Eylül 2022 |
Yayımlandığı Sayı | Yıl 2022 Cilt: 26 Sayı: 5 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.