期刊
2014 PROCEEDINGS OF THE 22ND EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO)
卷 -, 期 -, 页码 1681-1685出版社
IEEE
关键词
Pornography detection; binary descriptors; BossaNova representation; visual recognition
资金
- CNPq, Brazilian research and development agency
- CAPES , Brazilian research and development agency
- FAPEMIG, Brazilian research and development agency
- INCT InWeb
In certain environments or for certain publics, pornographic content may be considered inappropriate, generating the need to be detected and filtered. Most works regarding pornography detection are based on the detection of human skin. However, a shortcoming of these kind of approaches is related to the high false positive rate in contexts like beach shots or sports. Considering the development of low-level local features and the emergence of mid-level representations, we introduce a new video descriptor, which employs local binary descriptors in conjunction with Bossallova, a recent mid-level representation. Our proposed method outperforms the state-of-the-art on the Pornography dataset.
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