信息网络安全 ›› 2016, Vol. 16 ›› Issue (9): 184-191.doi: 10.3969/j.issn.1671-1122.2016.09.037

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特殊视频内容检测算法研究综述

任栋1, 宋伟1(), 于京2, 姜薇3   

  1. 1. 中央民族大学信息工程学院,北京 100081
    2. 北京交通大学电子信息工程学院,北京 100044
    3. 网络空间技术(北京)有限公司,北京 102200
  • 收稿日期:2016-07-25 出版日期:2016-09-20 发布日期:2020-05-13
  • 作者简介:

    作者简介: 任栋(1990—),男,山东,硕士研究生,主要研究方向为模式识别、视频内容检测;宋伟(1983—),男,湖北,讲师,博士,主要研究方向为图像处理、视频内容识别;于京(1971—),男,江苏,教授,博士,主要研究方向为图像处理;姜薇(1978—),女,北京,高级工程师,硕士,主要研究方向为网络信息安全。

  • 基金资助:
    国家自然科学基金[61503424];国家民委科研项目[14ZYZ017]

A Survey on Special Video Content Detection Algorithms

Dong REN1, Wei SONG1(), Jing YU2, Wei JIANG3   

  1. 1.School of Information Engineering, Minzu University of China, Beijing 100081, China
    2. School of Electronic Information Engineering, Beijing Jiaotong University, Beijing 100044, China
    3. Cyberspace Technology Limited Company, Beijing 102200, China
  • Received:2016-07-25 Online:2016-09-20 Published:2020-05-13

摘要:

网络流量的视频化趋势使得互联网视频内容呈现混杂化发展,各种非法特殊视频充斥其中,影响了社会公共安全,传统的通过视频源头进行控制的方式可行性较低,而建立内容检测过滤的方法将更为有效。为此,文章对色情、暴力、恐怖这三种特殊视频内容检测的研究现状和进展进行了综述。从三个角度,即视频内容描述模型、算法测试库、算法评判标准进行归纳和总结,详细介绍针对图像、视频等不同检测内容所采取的各种有效措施,对特征提取方法、分类检测策略及算法的检测效果进行了对比分析,之后对常用的算法测试库进行了整理,介绍不同测试库的数据量、数据特点及数据结构,同时介绍了视频内容检测方面几种常用的算法评判标准,最后对未来特殊视频检测技术的发展趋势进行了展望,以期为希望从事该领域研究的人员提供一些思路。

关键词: 内容检测, 特殊视频, 算法综述

Abstract:

Until now, research review of the special video content recognition algorithm has not yet appeared. But the network traffic has dominated by the video, and there are many types of contents, especial some illegal contents flooded the internet, which are affecting the social and public security. The traditional control methods which control the publishing of these videos are invalid, and the recognition model by content detection will be more effective. So, the survey of special content detection is given, and the summarization of the present work and developments about pornography, violence and terrorist videos content detection are presented. This paper has systematically surveyed the existing content detection algorithms from three aspects, and they are the content description model, the testing dataset, assessment criteria. Furthermore, combining with the current development of current technique, the research tendencies and the potential solutions are presented.

Key words: content identification, special video, algorithms survey

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