| 基于多特征的视频内容安全过滤方法 |
| |
| 引用本文： | 蒋呈明,蒋兴浩,孙锬锋. 基于多特征的视频内容安全过滤方法[J]. 信息安全与通信保密, 2012, 0(3): 76-77 |
| |
| 作者姓名： | 蒋呈明 蒋兴浩 孙锬锋 |
| |
| 作者单位： | 上海交通大学信息安全工程学院,上海,200240 |
| |
| 摘 要： | 应国家对视频网站加强有序管理的迫切要求，文中应用一种基于多模态特征的网络视频分类方法，实现对网络视频的安全监管。该方法对从网络视频中提取三大类的视频特征，分别针对音频特征、运动和颜色以及空间和时间特征，递进地对视频进行过滤。通过对视频中不良场景的定义，包括恐怖、暴力和色情语义，以检测网络视频内容中潜在的不良信息，实验证明该方法有效地提高了不良视频检测和分类的准确率。
|
| 关 键 词： | 多模态特征 视频分类 机器学习 安全监管 特征融合 |
Video Filtration for Content Security based on Multimodal Features |
| |
| JIANG Cheng-ming,JIANG Xing-hao,SUN Tan-feng. Video Filtration for Content Security based on Multimodal Features[J]. China Information Security, 2012, 0(3): 76-77 |
| |
| Authors: | JIANG Cheng-ming JIANG Xing-hao SUN Tan-feng |
| |
| Affiliation: | (School of Information Security Engineering,Shanghai Jiaotong University,Shanghai 200240,China) |
| |
| Abstract: | In order to meet the urgent requirement for management of video websites,an online video classification method based on multimodal features is designed and thereby the security supervision of the videos realized. This method filters the input videos by such different features as audio,color motion and space-time features in a specific order. Based on the definition of the illegal scenes,including horror,violence and pornography,the potential illicit information in videos is detected. Experiments show that this method can effectively improve the precision rate of detection and classification. |
| |
| Keywords: | multimodal features video classification machine learning security supervision feature fusion |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
