Multi-examples-learning-based method for identifying horror video scene

A multi-instance learning and video scene technology, which is applied in the field of horror video scene recognition based on multi-instance learning, can solve the problem of horror image filtering and so on

Active Publication Date: 2012-06-20
INST OF AUTOMATION CHINESE ACAD OF SCI
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although these existing studies do not directly target the filtering of terrorist i

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  • Multi-examples-learning-based method for identifying horror video scene
  • Multi-examples-learning-based method for identifying horror video scene
  • Multi-examples-learning-based method for identifying horror video scene

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Embodiment Construction

[0021] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0022] figure 1 The flow chart of the horror video scene recognition method based on the multi-instance learning algorithm provided by the present invention, such as figure 1 As shown, the horror video scene recognition method based on the multi-instance learning algorithm provided by the present invention specifically includes the following steps:

[0023] Step 1: Perform structural analysis on the video scene to obtain each shot in the video scene.

[0024] The structural analysis of the video scene further includes the following steps:

[0025] Step 1.1, perform shot segmentation on the video scene.

[0026] A shot detection method based on the mutual information entropy theory of information theory is used to detec...

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Abstract

The invention discloses a multi-examples-learning-based method for identifying a horror video scene. The multi-examples-learning-based method comprises the following steps of: carrying out shot segmentation and key frame selection on a video scene, wherein the video scene corresponds to a multi-examples learning bag, and a shot corresponds to the examples in the bag; respectively extracting visual characteristics, audio characteristics and color affective characteristics on the basis of the shot and a key frame to form a characteristic space; training a corresponding multi-examples learning classifier in the characteristic space; structurally analyzing a video sample to be tested, and extracting related characteristics; and predicting the category, namely horror or non-horror, of the video sample through the trained classifier. According to the invention, the novel color affective characteristics are provided and applied to the method for identifying the horror video scene, and the multi-examples-learning-based method has wide application prospect.

Description

technical field [0001] The invention relates to the field of pattern recognition and computer network content security, in particular to a horror video scene recognition method based on multi-instance learning. Background technique [0002] With the rapid development of Internet technology and applications, people's understanding and use of the Internet has become more and more in-depth. At the same time, the Internet has brought a lot of convenience to people's lives, and even changed people's way of life. On the basis of the rapid development of the Internet, the spread of harmful information such as pornography, violence, and terror has become easier and easier. Psychological and physiological studies have shown that terrorist information on the Internet is no less harmful to the physical and mental health of young people than pornographic information. Excessive terrorist information may cause people to be in extreme anxiety and fear for a long time, and even cause physi...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 胡卫明王建超李兵吴偶
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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