Key-frame extracting technology has been widely used in the field of human motion synthesis. Efficient and accurate key frames extraction methods can improve the accuracy of motion synthesis. In this paper, we use an optimized t-Stochastic Neighbor Embedding (t-SNE for short) algorithm to reduce the data and on this basis extract the key frames. The experimental results show that the validity of this method is better than the existing methods under the same experimental data.
