# Automatic TV Logo Identification for Advertisement Detection without Prior Data
## 6 Conclusions and Discussion  
This paper proposes a self-learning and automatic detection method for detecting television advertisement without using any prior data about the streams. The underlying assumption is that advertisement frames do not contain the channel logo; this is supported both by the state-of-the-art and the analysis performed over the collected dataset that demonstrated the high discriminating power of this visual feature. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Difficulty** & **Precision** & **Recall** & **F1** & **Accuracy** \\ \hline
1 & 89.3\% & 86.3\% & 85.6\% & 95.7\% \\
2 & 79.2\% & 93.6\% & 85.6\% & 90.3\% \\
3 & 48.7\% & 66.6\% & 55.7\% & 88.0\% \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Average results obtained for the sub-streams of the dataset, stratified by the difficulty level. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Method** & **Prec** & **TPR** & **F1** & **Acc** \\ \hline \multicolumn{5}{c}{SICNot\_BL stream} \\ [PERSON] et al. [3] & 100\% & 89.4\% & 94.4\% & 98.1\% \\ Our Proposal & 99.9\% & 99.8\% & 99.9\% & 99.9\% \\ \hline \multicolumn{5}{c}{TVI\_BL stream} \\ [PERSON] et al. [3] & 94.6\% & 93.2\% & 93.9\% & 95.1\% \\ Our Proposal & 100\% & 100\% & 100\% & 100\% \\ \hline \multicolumn{5}{c}{RTP\_BL stream} \\ [PERSON] et al. [3] & 100\% & 94.2\% & 97\% & 97.8\% \\ Our Proposal & 99.7\% & 99.8\% & 99.8\% & 99.8\% \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Comparison of the results obtained using the proposed method and the advertisement detection method proposed in [3]. The proposed solution automatically identifies candidate regions where the channel logo may be located and trains an object detector and partial sub-detectors using HOG features extracted from the logo location. The use of the partial detectors enables identification of the regions even in situations where the logo is only partially visible. The process is completely automatic as the extraction of training data is also controlled by the algorithm. For an objective assessment of the algorithm, a dataset comprised of multiple Portuguese and international channels was collected and annotated. Additionally, the streams were broken down in smaller segments of similar characteristics and assigned one of three difficulty levels. For a comparison with the state-of-the-art, the current proposal was also assessed on the testing dataset of a state-of-the-art advertisement detection method. Even though the advertisement detection may be impaired by abnormal situations, such as the channel logo becoming invisible due to background absorption or because of self-advertising, results show that the proposed method surpasses the state-of-the-art, achieving significant performance on multiple types of streams, including those of greater complexity. The current proposal may benefit of additional work at the level of postprocessing to increase detail in relevant regions and circumvent some of the missed detections due to the absorption of the logo by the background. Besides using the channel logo, performance may also be improved by incorporating the detection of other visual features, even if these have lower discriminating power, and specially by also using audio in a multimodal approach. Conceptualization, A.P., P.V. and P.C. ; methodology, A.P., P.V. and P.C. ; software, A.P. ; validation, A.P. and P.C. ; formal analysis, A.P. and P.C. ; investigation, A.P. and P.C. ; resources, A.P. and P.C. ; data curation, A.P. ; writing--original draft preparation, A.P. and P.C. ; writing--review and editing, A.P., P.V. and P.C. ; visualization, A.P., P.V. and P.C. ; supervision, P.V. and P.C. ; project administration, P.C. ; funding acquisition, P.V. and P.C. All authors have read and agreed to the published version of the manuscript. The work presented was financed by National Funds through the Portuguese funding agency, FCT--Fundacao para a Ciencia e a Tecnologia, within project UIDB/50014/2020. Not applicable. Not explicitly. * [PERSON] et al.