Video frequency advertisement recognition method based on layered matching

Abstract

The present invention relates to a video advertisement identifying method based on hierarchical matching. Through locality sensitive hash (LSH) and fine granularity successive elimination (FGSE), the method which can rapidly inspect whether TV programming contains the advertisements as listed in database is developed by utilizing the novel video features of advertisements and post-treatment technology. The technical proposal is that the present invention is characterized in comprising the following steps of the establishment of offline database and online monitoring, wherein, the offline database consists of offline pre-treatment and Hash form preparation; the online monitoring consists of online pre-treatment, from-coarse-to-fine secondary matching and post-treatment.

Description

technical field [0001] The invention belongs to the field of video advertisement identification methods, in particular to a video advertisement identification method based on hierarchical matching. Background technique [0002] With the advancement of science and information technology, especially the continuous development of computer technology, network technology and large-capacity storage technology, people have used various means to collect and produce a large number of various types of multimedia information data. Multimedia has become the main component of transmitting data on the information superhighway. Among these multimedia information, digital media combines vision and hearing, effectively provides a large amount of information to people, and has important application and research value. [0003] In the multimedia data stream, both structured data and unstructured data are included. In addition to traditional text and numbers in multimedia data, other data typ...

AI Technical Summary

Problems solved by technology

But because ads are multi-formatted, and the differences between ads with different styles are also very obvious, it is difficult to find a common distinguishing feature

In addition, the detection system may be sensitive to certain thresholds, so it is difficult to find a unified set of thresholds for all types of videos

Moreover, such methods rely too much on the laws and regulations of various countries, cutting methods, and production styles of various programs, and cannot form a general TV monitoring system.

The accuracy rate and recall rate of monitoring are often interfered by some programs with similar visual information or auditory information, and the accuracy rate and recall rate are often not high

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