# Best Frame Selection to Enhance Training Step Efficiency in Video-Based Human Action Recognition
## 4 Result and Discussion
### Implementation Details
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline \multicolumn{2}{c}{**UCF101**} \\ \hline \multirow{2}{*}{**Method**} & \multirow{2}{*}{**Pre-Processing Type**} & \multirow{2}{*}{**None**} & \multicolumn{4}{c}{**Different \(P_{\textit{trresh}}\) Values**} \\ \cline{3-8}  & & & **0.06** & **0.08** & **0.1** & **0.12** & **0.14** \\ \hline \multirow{2}{*}{Two-Stream I3D [30]} & Train & 93.5 & 93.3 & 93.9 & 95.6 & 93.2 & 93.6 \\ \cline{2-8}  & Test & 92.5 & 91.2 & 92.3 & 93.1 & 93 & 92.2 \\ \hline \multirow{2}{*}{Motion Guided Network [31]} & Train & 96.4 & 93.8 & 94.9 & 97.2 & 97.4 & 95.4 \\ \cline{2-8}  & Test & 94.1 & 92.6 & 93.6 & 95.1 & 95.1 & 94.4 \\ \hline \multirow{2}{*}{Spatiotemporal network [32]} & Train & 94.7 & 94.3 & 94.4 & 97.4 & 94.7 & 95.3 \\ \cline{2-8}  & Test & 93.8 & 92.5 & 93.6 & 94.7 & 94.1 & 93.3 \\ \hline \multirow{2}{*}{Correlation net [33]} & Train & 96 & 97 & 97 & 98 & 95.5 & 95 \\ \cline{2-8}  & Test & 92.8 & 94.9 & 95.2 & 95.2 & 95 & 94.6 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Accuracy of the Train and Test data in UCF101 dataset in Different \(P_{\textit{trresh}}\) values. \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline \multicolumn{2}{c}{**HMDB51**} \\ \hline \multirow{2}{*}{**Method**} & \multirow{2}{*}{**Pre-Processing Type**} & \multirow{2}{*}{**None**} & \multicolumn{4}{c}{**Different \(P_{\textit{trresh}}\) Values**} \\ \cline{3-8}  & & & **0.06** & **0.08** & **0.1** & **0.12** & **0.14** \\ \hline \multirow{2}{*}{Two-Stream I3D [30]} & Train & 72.1 & 75.3 & 72.8 & 76.1 & 72.6 & 68.2 \\ \cline{2-8}  & Test & 65.2 & 68 & 68.3 & 68.5 & 67.6 & 67.3 \\ \hline \multirow{2}{*}{Motion Guided Network [31]} & Train & 72.3 & 73.7 & 71.2 & 77.4 & 78 & 75.2 \\ \cline{2-8}  & Test & 68 & 69 & 69.3 & 70.3 & 69.9 & 69.8 \\ \hline \multirow{2}{*}{Spatiotemporal network [32]} & Train & 67.3 & 68.2 & 68.6 & 69.8 & 73.3 & 68.1 \\ \cline{2-8}  & Test & 66.4 & 66.5 & 66.8 & 67.4 & 66.6 & 65.9 \\ \hline \multirow{2}{*}{Correlation net [33]} & Train & 73 & 75.7 & 78 & 74.7 & 73.8 & 71.2 \\ \cline{2-8}  & Test & 68.1 & 70.1 & 70.7 & 70.7 & 69.9 & 69.6 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Accuracy of the Train and Test data in HMDB51 dataset in Different \(P_{\textit{trresh}}\) values. \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multicolumn{2}{c}{**Method Dataset**} & \multicolumn{4}{c}{**HMDB51**} & \multicolumn{4}{c}{**UCF101**} \\ \hline \multirow{2}{*}{Two-Stream I3D [30]} & Train & 72.1 & 76.1 & 93.5 & 95.6 \\ \cline{2-8}  & Test & 65.2 & 68.5 & 92.5 & 93.1 \\ \hline \multirow{2}{*}{Motion Guided Network [31]} & Train & 72.3 & 77.4 & 96.4 & 97.2 \\ \cline{2-8}  & Test & 68 & 70.3 & 94.1 & 95.1 \\ \hline \multirow{2}{*}{Spatiotemporal network [32]} & Train & 67.3 & 69.8 & 94.7 & 97.4 \\ \cline{2-8}  & Test & 66.4 & 67.4 & 93.8 & 94.7 \\ \hline \multirow{2}{*}{Correlation net [33]} & Train & 73 & 74.7 & 96 & 98 \\ \cline{2-8}  & Test & 68.1 & 70.7 & 92.8 & 95.2 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Total accuracy obtained by the HAR systems under study with the tuned proposed method. Therefore, it is possible to conclude that the proposed method can be added to the beginning of any HAR system that uses random frame selection in order to improve the accuracy of the final system.