• AI to spot violent and adult videos

    02.05.2017 Interviews

    Last week, after a tragic Thai video appeared on Facebook and Youtube, we received a request from Reuters Asia asking to briefly address some questions regarding the state of visual content filtering industry. A part of the interview was briefly mentioned in the Reuters’ article. In this blog post we are publishing a full version.

    Reuters: What technology do you offer to automatically filter out undesirable content — violence, pornography? Could you provide a bit of background about how it works, and how it differs to other companies’ offerings?

    Michael Pogrebnyak, Kuznech CEO: Detection of pornography is a significant subtask of content filtering problem on the internet. Studies have estimated that of the world’s 42 million websites, 12% contain adult content. Another statistical result estimated 70% of teens have unintentionally come across pornography on the web. This is, of course, alarming. The problem of detecting an adult-oriented content in images still remains unsolved and is widely addressed by many researchers. Over the past years there have been many approaches to detect and filter pornography.

    Classification of porn video has been done by combining image features and motion information (Jansohn, Ulges, Breuel, 2008), repetitive motion detection (Endeshaw, Garcia, Jakobsson, 2008), skin detection (Stottinger, Hanbury, Liensberger, Khan, 2009), skin detection in an image to classify human body by applying geometric patterns (Fleck, Forsyth, Bregler, 1996), skin detection with using erotogenic-parts (Shen, Wei, Qian, 2007), features of previews (Rasheed, Shah, 2009), breast detection (Wang, Hu, Yao, 2009), complex method based on camera motion, skin detection and image features (Torres, 2012).

    To contribute to solving the problem, Kuznech proposes an innovative approach based on logotype detection, text recognition and scene classification by convolutional neural networks (CNN)…