# Image Analysis Using Human Body Geometry and Size Proportion Science for Action Classification
## 4 Results and Discussion
### Results  
In this subsection, experimental results are presented when the proposed technique is applied on action image dataset. Figure 5 is showing the results through each step of proposed technique. Table 2 is showing a classification matrix, representing statistical results in the case when the proposed technique is applied over Daria images. Originally, 278 images of [PERSON] having all the six actions were tested. The proposed technique achieved 100%, 96.3%, 83.1%, 86.9%, 91.2%, and 100% recall for SHSW, SHTW, walk, standing, BHSW, and BHTW actions, respectively, while there were  
Figure 5: Results of each step through the proposed technique. 100%, 92.9%, 92.5%, 81.5%, 100%, and 93% precision values for them, respectively. An overall accuracy of 91.4% is achieved while, out of all the images, 9 remained un-classified. Table 3 is a classification matrix for the six defined actions achieved after implementing the proposed technique using the Denis images. A total of 188 images having all the six actions were tested and, out of those 188 images, 10 were un-classified while from the remaining 178 images 91.6% actions were accurately classified giving 100%, 95%, 81.9%, 91.7%, 100 %, and 100% recall and 100%, 82.6%, 100%, 80.0%, 100%, and 100% precision for SHSW, SHTW, walk, standing, BHBW, and BHTW actions, respectively. The classification matrix for Ira images is shown in Table 4. In this experiment, a total of 267 images are tested to evaluate the proposed technique. The unclassified images are 18 while the rest of the 249 images are classified. The overall accuracy for Ira actions is 93.2% while 93.9%, 92.9%, 86.2%, 100%, 90.9%, 90.9% recall and 91.2%, 95.1%, 100%, 87.8%, 100%, and 90.9% precision for SHSW, SHTW, walk, standing, BHBW and BHTW actions, respectively, are achieved. In Table 5, classification results for \"Eli\" have been presented showing precision, recall, overall accuracy, and other evaluation metrics. It may be observed that a total of 281 images of Eli are tested that contained all the six actions. A total of 273 images are classified leaving eight of them unclassified. Overall classification accuracy over Eli images is 91.7% while 8.3% actions are misclassified. There is 98.2%, 89.2%, 92.3%, 86%, 95.7%, and 85.2% recall, and 100%, 92.6%, 95.6%, 71.2%, 100%, and 95.8% precision for SHSW, SHTW, walk, standing, BHBW, and BHTW actions, respectively, is recorded. Least precision is for standing action while the least recall is for BHTW with an 85.2% score. \begin{table}
\begin{tabular}{l c c c c c c c c c c c c} \hline \hline  & **SHSW** & **SHTW** & **Walk** & **Standing** & **BHSW** & **BHTW** & **Total Images** & **Recall** & **Classification** & **Theal** & **In-Classified** & **Theal** & **In-Classification** \\ \hline _SHSW_ & **31** & 2 & 0 & 0 & 0 & 0 & 33 & 93.9\% & 6.1\% & 1 & 34 & 2.9\% \\ _SHTW_ & 3 & **39** & 0 & 0 & 0 & 0 & 42 & 92.9\% & 7.1\% & 7 & 49 & 14.5\% \\ _Walk_ & 0 & 0 & **80** & 8 & 0 & 58 & 86.2\% & 13.8\% & 1 & 59 & 1.7\% \\ _Stanlay_ & 0 & 0 & 0 & **72** & 0 & 0 & 72 & 100.\% & 0\% & 3 & 75 & 4.0\% \\ _BHSW_ & 0 & 0 & 0 & **20** & 2 & 22 & 90.9\% & 9.1\% & 4 & 26 & 15.4\% \\ _BHTW_ & 0 & 0 & 0 & 2 & **20** & 22 & 90.9\% & 9.1\% & 2 & 24 & 8.3\% \\ _Total_ & 34 & 41 & 50 & 82 & 20 & 22 & n - 249 & & 18 & m - 287 & Overall Un Classification(8,7\%) \\ _Precision_ & 91.2\% & 95.1\% & 100\% & 87.8\% & 100\% & 90.9\% & Overall Accuracy(90.2\%) & & & & \\ _Constant_ & 8.5\% & 4.9\% & 0.0\% & 12.2\% & 0\% & 9.1\% & & & & \\ _Error_ & 8.5\% & 4.9\% & 0.0\% & 12.2\% & 0\% & 9.1\% & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Classification matrix for Ira images.