Abstract
Despite the efficient solutions in pornography detection literature, specific solutions for sensitive content in cartoons have not been developed yet. In this work, we evaluate how state-of-the-art solutions for natural videos (with humans) perform in cartoons. Also, we propose a new method with higher accuracy, showing that treating cartoons independently can improve sensitive content filtering.
Highlights
Children that have grown up with technology, the socalled “digital natives”, spend most of their recreation time on the internet, commonly watching cartoons
Another study showed that 30% of all content on the web is pornographic [2], making it easy for kids to watch porn cartoons accidentally
As a first to explore the sensitive cartoons problem, we built a database with 544 non-porn cartoons and 195 porn cartoons
Summary
Introduction Children that have grown up with technology, the socalled “digital natives”, spend most of their recreation time on the internet, commonly watching cartoons. According to the United Nations Children's Fund (UNICEF), children and teenagers represent (in 2016) one in three users on the internet [1]. Another study showed that 30% of all content on the web is pornographic [2], making it easy for kids to watch porn cartoons accidentally. We have vast literature in pornography detection, the solutions are all focused on videos with humans (natural videos).
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