Network violent video identification method

Abstract

The invention discloses a network violent video identification method based on multiple examples and multiple characteristics. The method for identifying the network violent videos comprises the steps of grasping violent videos, non-violent videos, comments on the violent videos, comments on the non-violent videos, brief introductions of the violent videos and brief inductions of the non-violent videos from a video sharing network, and structuring a video data training set; extracting textural characteristics from textural information of the training set, forming textural characteristic vectors to train a textural pre-classifier, and screening out candidate violent videos by using the pre-classifier; using a shot segmentation algorithm based on a self-adapting dual threshold for conducting segmentation on video segments of the candidate violent videos, extracting related visual characteristics and voice frequency characteristics of each scene to express the scene, taking each scene as an example of multi-example study, and taking video segments as a package; and using an MILES algorithm for converting the package into a single example, using a characteristic vector for training a classifier model, and using the classifier model for conducting classification on the candidate violent videos. By the utilization of the network violence video identification method, bad influences that the network violent videos are broadcasted without constrain are largely lightened.

Description

technical field [0001] The invention relates to the field of pattern recognition and computer network content security, in particular to the problem of video classification. 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. Through the Internet, people can obtain rich information and knowledge, communicate conveniently, and enjoy various entertainment activities. However, the Internet is open, and the massive amount of information it carries must have adverse effects, such as pornography, violence, terror and other harmful information are also widely spread along the Internet. The minors are in the growth stage physically and psychologically, and are vulnerable to the bad influence of the outside world. Some even embarked on the road of crime and caused many social problems. Teenagers are on the wrong track. Video sites have sprung up like mushr...

AI Technical Summary

Problems solved by technology

The research objects of these violent video recognition methods are mostly video clips of one movie or several movies, and the amount of data is small. However, for the massive video data on the network, the performance and processing speed of these methods are reduced to varying degrees.

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