Pornographic video detection method based on semi-supervised learning of images

A semi-supervised learning and video detection technology, applied in instruments, character and pattern recognition, computer parts, etc., can solve the problems of complex background, inaccurate detection results, and incomplete extraction of foreground areas.

Inactive Publication Date: 2013-11-20
XI AN JIAOTONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the complex background and the inconspicuous movement of the target in a short period of time,

Method used

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  • Pornographic video detection method based on semi-supervised learning of images
  • Pornographic video detection method based on semi-supervised learning of images
  • Pornographic video detection method based on semi-supervised learning of images

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Embodiment Construction

[0040] The implementation of the present invention will be described in detail below in conjunction with the examples.

[0041] A pornographic video detection method based on graph semi-supervised learning, the steps are as follows:

[0042] Step 1, foreground area extraction based on motion information, the steps are as follows:

[0043] a) Detect the shot boundary in the video based on the dual domain value algorithm.

[0044] Extract the histogram information of the three components of R, G, and B in the video frame, and calculate the difference value of the histogram of adjacent frames. Calculated as follows:

[0045] Z ( k , k + 1 ) = 1 M Σ i ∈ { R , G , B ...

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Abstract

The invention relates to a pornographic video detection method based on semi-supervised learning of images. The method comprises the steps of first carrying out shot segmentation on a video, acquiring a key frame in a shot, carrying out inter-frame difference on the key frame and an adjacent multi-frame image, extracting a partial motion foreground area, wherein the key frame is an intermediate frame in the shot, then using the extracted area as prior information for acquiring a real foreground area, extracting a complete foreground area by adopting the method based on semi-supervised learning of images and segmenting a skin color area in the complete foreground area, identifying harmful key frames based on characteristics of the skin color area, and carrying out judgment on harmful video content. According to the invention, the partial motion foreground area is acquired by the aid of an inter-frame difference method, the area is used as the prior information, the complete foreground area is extracted by adopting the method based on semi-supervised learning of images, and then carrying out pornographic content detection on the extracted foreground area.

Description

technical field [0001] The invention belongs to the field of computer applications and relates to pornographic video detection, in particular to a pornographic video detection method based on graph semi-supervised learning. Background technique [0002] With the rapid development of the Internet and multimedia technology, video media in the network is ubiquitous and has become an important part of our life and entertainment. However, it is filled with a large number of pornographic videos, which has caused extremely serious negative impacts on social and cultural life. How to effectively prevent the spread of pornographic videos on the Internet is of great significance to maintaining the physical and mental health of young people and purifying network video resources. [0003] Over the past few years, methods for pornographic video detection have emerged. These methods are divided into three categories: the first category is to extract the key frames of the video, and dete...

Claims

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Application Information

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IPC IPC(8): G06K9/66G06K9/36G06K9/00
Inventor杜友田余伟郑庆华陶敬周亚东秦涛
OwnerXI AN JIAOTONG UNIV