The same set of pictures as the test group where given to the computer for analysis. Table 4 shows the results and average for each picture. Each picture was again analysed three times and from that the average was calculated. As with test phase one, the average rating for each picture was divided by the region of interest (the area the algorithm uses for facial feature detection). The resulting calculation is the smile estimation (The spread sheet from test phase two, computer results, can be found in Appendix 16.4) Table 4 - Test Phase Two - Computer Results Computer Run Run1 Run2 Run3 Average Roi Smile Estimation 1 16.66544687 16.56030518 94 2 23.02456359 22.9198501 22.68040995 135 1.69444009 3 12.42981214 11.70685245 75 4 16.28649313 15.72480991 105 5 17.36557765 16.42881525 121 6 21.31739475 20.745321 21.51129831 119 7 15.57627663 16.29680304 102 8 10.78660505 10.9531507 64 9 14.94659186 14.99589758 87 10 10.62019061 10.56063579 64 The following graphs show the plotted data from test phase two – test subjects and test phase two – computer. The value of the x-axis corresponds to the picture number and the value of the y-axis corresponds to the rating. As can be seen on the graphs, by selecting pictures that perfectly match the abilities of the algorithm, the results by the computer and test subjects are almost equal. The algorithm therefore functions accordingly to being able to precisely estimate the level of smile in each picture. Although the estimations by the computer have not been normalised, the valleys and peaks from both graphs (discounting the intensity) follow the same path. Therefore compared to the results from test phase one, the results in test phase two show that the program was able to correctly estimate the level of smile in each picture as the graphs fluctuate the same.
The same set of pictures as the test group where given to the computer for analysis. Table 4 shows the results and average for each picture. Each picture was again analysed three times and from that the average was calculated. As with test phase one, the average rating for each picture was divided by the region of interest (the area the algorithm uses for facial feature detection). The resulting calculation is the smile estimation (The spread sheet from test phase two, computer results, can be found in Appendix 16.4) Table 4 - Test Phase Two - Computer Results Computer Run Run1 Run2 Run3 Average Roi Smile Estimation 1 16.66544687 16.56030518 94 2 23.02456359 22.9198501 22.68040995 135 1.69444009 3 12.42981214 11.70685245 75 4 16.28649313 15.72480991 105 5 17.36557765 16.42881525 121 6 21.31739475 20.745321 21.51129831 119 7 15.57627663 16.29680304 102 8 10.78660505 10.9531507 64 9 14.94659186 14.99589758 87 10 10.62019061 10.56063579 64 The following graphs show the plotted data from test phase two – test subjects and test phase two – computer. The value of the x-axis corresponds to the picture number and the value of the y-axis corresponds to the rating. As can be seen on the graphs, by selecting pictures that perfectly match the abilities of the algorithm, the results by the computer and test subjects are almost equal. The algorithm therefore functions accordingly to being able to precisely estimate the level of smile in each picture. Although the estimations by the computer have not been normalised, the valleys and peaks from both graphs (discounting the intensity) follow the same path. Therefore compared to the results from test phase one, the results in test phase two show that the program was able to correctly estimate the level of smile in each picture as the graphs fluctuate the same.