Please use this identifier to cite or link to this item:
|Type:||Artigo de evento|
|Title:||Pornography Detection Using Bossanova Video Descriptor|
De Araujo A.A.
|Abstract:||In certain environments or for certain publics, porno-graphic 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 BossaNova, a recent mid-level representation. Our proposed method outperforms the state-of-the-art on the Pornography dataset.|
|Editor:||European Signal Processing Conference, EUSIPCO|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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