# Unsupervised 3D Motion Summarization Using Stacked Auto-Encoders
## 6 Experimental Results
### Dance Summarization Experiments
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{\
\begin{tabular}{c} **Summarization Algorithm** \\ \end{tabular} } & \multirow{2}{*}{**Aver. Shift**} & \multirow{2}{*}{**Aver. Shift**} & \multirow{2}{*}{**Improvement**} & **Aver. Shift** & **Aver. Shift** & **Improvement** \\  & & & **With SAE** & & **Ratio** & **Without SAE** & **With SAE** & **Ratio** \\  & **(Single Dancer)** & **(Single Dancer)** & **(Single Dancer)** & **(Two Dancers)** & **(Two Dancers)** & **(Two Dancers)** & **(Two Dancers)** \\ \hline \hline \multirow{2}{*}{
\begin{tabular}{c} KenStone \\ K-OPTICS \\ SMRS \\ \end{tabular} } & 0.51 & 0.47 & 6.96\% & 1.67 & 0.84 & 49.79\% \\  & 0.51 & 0.51 & 0.67\% & 1.28 & 2.29 & 79.15\% \\  & 0.47 & 0.41 & 11.41\% & 1.73 & 1.03 & 40.55\% \\ H-SMRS & 0.45 & 0.31 & 31.15\% & 1.44 & 0.26 & 81.80\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The improvement ratio among the adopted summarization algorithms with and without the SAE framework for Syrtos (3b) dance sequence. Two different performances of the dance are assumed; one for a single dancer and one for two dancers. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{\begin{tabular}{c} **Summarization Algorithm** \\ \end{tabular} } & \multirow{2}{*}{**Dance**} & \multirow{2}{*}{\begin{tabular}{c} **Average** \\ **Shift with** \\ **SAE** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Average** \\ **Shift with** \\ **without SAE** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Standard** \\ **Deviation** \\ **with SAE** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Standard** \\ **Deviation** \\ **without SAE** \\ \end{tabular} } \\ \hline \hline \multirow{2}{*}{\begin{tabular}{c} KenStone \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} Makedonikos \\ Syrtos (2b) \\ Syrtos (3b) \\ \end{tabular} } & 0.46 & 0.38 & 0.78 & 0.64 \\  & & 0.27 & 0.19 & 0.17 & 0.12 \\  & & 0.84 & 1.67 & 1.4 & 2.41 \\ \hline \hline \multirow{2}{*}{\begin{tabular}{c} SMRS \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} Makedonikos \\ Syrtos (2b) \\ Syrtos (3b) \\ \end{tabular} } & \multirow{2}{*}{0.25} & 0.59 & 0.17 & 1.21 \\  & & 0.19 & 0.23 & 0.17 & 0.12 \\  & & 1.03 & 1.73 & 2.74 & 2.35 \\ \hline \hline \multirow{2}{*}{\begin{tabular}{c} K-OPTICS \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} Makedonikos \\ Syrtos (2b) \\ Syrtos (3b) \\ \end{tabular} } & \multirow{2}{*}{0.53} & 0.65 & 0.96 & 1 \\  & & 0.34 & 0.36 & 0.23 & 0.23 \\  & & 1.28 & 2.29 & 2.31 & 3.91 \\ \hline \hline \multirow{2}{*}{\
\begin{tabular}{c} H-SMRS \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} Makedonikos \\ Syrtos (2b) \\ Syrtos (3b) \\ \end{tabular} } & \multirow{2}{*}{0.24} & 0.54 & 0.18 & 1.06 \\  & & 0.23 & 0.24 & 0.18 & 0.12 \\ \multicolumn{2}{c}{} & & 0.26 & 1.44 & 0.19 & 2.14 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Average time shift among the summarization outcomes and the experts’ annotations with and without the Stacked Auto-Encoder (SAE)-based data compression scheme. Figure 11 provides further insights on the similarity among extracted key frames, using summarization algorithms, and some user annotated (selected) key frames. This allows us to _visually_ judge on the similarity between the key frames extracted by the summarization algorithms and the ground truth ones. The results demonstrate five basic postures from Makedonikos dance. Then, for each the four summarization approaches, we select the closest frame to the user annotated posture of reference. As is observed, H-SRMS selections are closer to the experts' defined key frames, compared to K-OPTICS, SMRS, and KenStone approaches. Figure 12 demonstrates the encoding capabilities for the adopted SAE scheme. Recall that 400 values have been reduced to 48 and then reconstructed back using SAEs.