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Type: Artigo de evento
Title: Pornography Detection Using Bossanova Video Descriptor
Author: Caetano C.
Avila S.
Guimaraes S.
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
Rights: fechado
Identifier DOI: 
Date Issue: 2014
Appears in Collections:Unicamp - Artigos e Outros Documentos

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