Study on the Recognition of Objectionable Audio
Study on the Recognition of Objectionable Audio
复制标题
DOI：
10.1142/s0218001410008238
复制
发表时间：
2010-09
期刊：
影响因子：
--
通讯作者：
Ziqiang Shi;Boyang Gao;Tieran Zheng;Jiqing Han
中科院分区：
文献类型：
--
作者：
Ziqiang Shi;Boyang Gao;Tieran Zheng;Jiqing Han
本文提出了一种新的方法，从特征-声音识别-的角度来自动检测成人视频序列，它可以作为一个验证步骤，一个补充方法或独立的检测器。针对色情音的特殊性，对其进行了特征分析。基于流行的功能，直方图和轮廓作为新的功能集。同时，由于外部数据的复杂性，提出了一种称为类内聚类的通用框架，选择最具代表性的子类进行训练和分类。所有这些努力都提高了召回率，降低了误报率。在互联网上真实的数据集上的实验表明，该方法具有上级性能，召回率为89.17%，误报率为10.78%.
In this paper, a novel method from the feature — porno-sounds recognition — point of view is proposed to detect adult video sequences automatically which may serve as a verification step, a supplementary method or an independent detector. To the specificity of erotic sound, its feature analysis is given. Based on the popular features, histograms and contours are introduced as new sets of features. At the same time due to the complexity of outside data, a general framework called in-class clustering is proposed which selects the most representative subclass for training and classification. All these efforts increase the recall rate and decrease the false positive rate. Experiments on real data from the Internet indicate that the proposed method yields superior performance with 89.17% recall rate and 10.78% false positive rate being achieved.