Video content quick retrieving method based on object tag

Abstract

The invention provides a video content quick retrieving method based on an object tag. The method comprises the following steps: extracting and analyzing the color feature, contour feature, scene feature and character feature of a moving object in each image frame of a video; processing a plurality of pictures of known types by using the feature extraction method, and training a contour classifier and a scene classifier by using the contour features and scene features of the pictures; processing a video to be retrieved by using the feature extraction and analysis method and the classifiers soas to generate type tags of objects in each image frame of the video, wherein the type tags are used for constructing an object tag database; and retrieving a response server to search the object tagdatabase to find videos related to a query request submitted by a user, and generating an ordered result for the user to browse and refer. The method provided by the invention can be used for retrieving the video content at a speed similar to that of the conventional text retrieval only by searching the object tag database and achieving the fine granularity retrieval of the video content, so thatthe method is more accurate than the conventional method.

Description

technical field [0001] The invention relates to computer image processing technology and video information processing technology, specifically including feature extraction, analysis, identification and data modeling technology of video, color, geometric ratio, subtitle, object type and scene. Background technique [0002] Video data acquisition terminal equipment such as cameras and video surveillance machines have been widely used in many fields such as national defense projects, urban security, public safety, traffic management, and home life. According to incomplete statistics, there are tens of thousands of surveillance cameras and video cameras used in general modern cities in China, and the number is doubled and replaced every year. Corresponding to such a large number of video devices is a massive amount of video data, such as surveillance videos of military management areas, community security surveillance videos, collection videos of public security investigations, ...

AI Technical Summary

Problems solved by technology

The object retrieved by this type of technology belongs to the coarse-grained content of the video, and it is difficult to meet the needs of many fine-grained video content retrieval, such as retrieving suspects with certain clothing color characteristics, a certain type of vehicle involved in an accident, etc.

At the same time, this video retrieval method will also encounter the above-mentioned time bottleneck problem

Images