Massive video abstraction generation method based on cluster and H264 video concentration algorithm

Abstract

The invention discloses a massive video abstraction generation method based on a cluster and H264 video concentration algorithm. The method comprises the following steps: (1), an original video is selected and is cut to obtain n segments with approximately equal length, wherein the coding format is H264 and the n is a natural number; (2), video decoding is carried out on all cut segments, a foreground target is obtained according to motion estimation and a background picture, detection rates of all segments are perfected according to a sparse- optical-flow-based misinformation deletion and leak detection repairing algorithm, and the background picture is updated; and (3), the single segment containing the motion information is used as a concentration unit to carry out compression, splicing is carried out after compression completion, and then a complete video abstract is generated.

Description

technical field [0001] The invention belongs to the technical field of mass video data concentration, in particular to a method for generating mass video summaries based on cluster and H264 video concentration algorithms. Background technique [0002] As we all know, video surveillance systems are penetrating into various social occasions, and are playing an increasingly important role in many industries such as security, transportation, industrial production and other environments; with the rapid increase in the number of surveillance cameras, every day A large amount of video data is also generated. At present, most of these videos are manually browsed and meaningful information is extracted. [0003] On the one hand, the more videos, the more people are needed; on the other hand, the efficiency of manual processing will become lower due to more and more data, and the processing results will inevitably be missed or have errors; however, the processing cost Quite impressiv...

AI Technical Summary

Problems solved by technology

[0004] Video summarization is also known as video enrichment. The processing process of this technology is usually: firstly, obtain the foreground object through background modeling; then use the tracking algorithm to save the motion trajectory; finally, combine the trajectory of the object in a certain way and copy it to the background image , to form a condensed video; however, the length of the video condensed by the existing video condensing technology is generally much smaller than the original video. If there is a high-definition video with a duration of 10 hours, the usual background modeling algorithm, such as GMM, runs at about It is equal to the real-time playback speed. If you want to browse the entire condensed video, it will also consume 10 hours, but the efficiency has not been greatly improved.

Images