## 4 Experimental Results and Analyses
### Experiment on Image-Query-Based Video Searching
#### 4.3.3 Experiment on Our Video Searching and Fingerprint Detection Dataset
The highest video searching accuracy is 0.94 and the shot searching accuracy is 0.82. However, under most conditions, the shot searching accuracies are less than 0.8. The first comparison experiment was conducted by using a bigger image size: 256 \(\times\) 256. A larger image size conveys more content information; in theory, the video searching results from using \begin{table}
\begin{tabular}{c c} \hline
**Parameters** & **Value** \\ \hline Image resize for feature extraction & 128 \(\times\) 128; 256 \(\times\) 256 \\ Select frames in a shot & three frames (first frame, middle frame, last frame); \\  & step skip frames (step skip by a quarter of the frame rate) \\  & SIFT; Speed Up Robust Features (SURF) \\  & UBCMATCH threshold1 & [1.2, 1.4, 1.6, 1.8, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0, 3.2, 3.4] \\  & [2, 3, 4, 5, 6, 7, 8, 9] \\ \hline \end{tabular}
\end{table} 
Table 20: The experimental parameters. \begin{table}
\begin{tabular}{c c c c c c} \hline
**ID\_AT** & **Attack Types** & **Sample Attacked Image** & **ID\_AT** & **Attack Types** & **Sample Attacked Image** \\ \hline AT1 & VT1 & AT6 & VT5\(\rightarrow\)VT6\(\rightarrow\)VT3 & \\ \hline AT2 & VT2\(\rightarrow\)VT3 & AT7 & VT7 & \\ \hline AT3 & VT1\(\rightarrow\)VT2\(\rightarrow\)VT3 & AT8 & VT7\(\rightarrow\)VT4\(\rightarrow\)VT5 & \\ \hline AT4 & VT4\(\rightarrow\)VT5 & AT9 & V10\(\rightarrow\)VT8 & \\ \hline AT5 & VT1\(\rightarrow\)VT4\(\rightarrow\)VT5 & AT10 & VT9\(\rightarrow\)V10 & \\ \hline \end{tabular}
\end{table} 
Table 19: The performed attacks on the test images for video searching. features extracted from larger-size images will be larger. The only difference in the control group is the image size. The results of video searching and shot searching are shown in Figure 17. Compared to Figure 16, the video searching accuracies and shot searching accuracies are both increased. The shot searching accuracies rise to a greater extent than the video searching accuracies. According to the results, using a larger-size image for feature extraction improves the performance by 0.01-0.03 on average compared to using a smaller-size image. However, the computing time under a larger-size image has been increased a lot not only for feature extraction but also for video searching. Figure 16: The experimental results with the control group. (**a**) Video searching; (**b**) Shot searching. Figure 17: _Cont._  
The second comparison experiment adopted different frame selection methods to select the frame numbers in a shot for feature extraction. The only difference in the control group is the use of the three frames method instead of the step skip frames method. The results of video searching and shot searching are shown in Figure 18. Compared to Figure 16, the results show that three-frames-based feature selection for a shot is much worse than step skip frames-based feature selection. The highest video searching accuracy of the three frames method is lower than 0.9 and its downward trends fall faster. The video searching accuracies have decreased by at least 0.05 and the highest value has dropped by 0.07. The shot searching accuracies have also gone down. The highest shot searching accuracy is less than 0.8. Although the three frames method is simpler and has a shorter computation time, the results of it are not satisfactory, especially on video searching. Consequently, the step skip frames method should be considered instead of the three frames method in further experiments. Figure 17: The experimental results by using different size images. (**a**) Video searching; (**b**) Shot searching. Figure 18: _Cont._  
The third comparison experiment used different feature descriptors. Since the SURF descriptor is faster and also works well in many applications, it can be used instead of SIFT. The results of video searching and shot searching are shown in Figure 19. To show the result more clearly, the results under lower UBCMATCH thresholds (1.2 and 1.4) are not shown. Compared to Figure 16, the results show that the SIFT method has far better performance than SURF.