Method for realizing quick retrieval of mass videos

Abstract

The invention relates to a method for realizing the quick retrieval of mass videos. The method comprises the following steps: respectively extracting spatial feature vectors from all frame video images in a video stream of a video library to obtain video feature sequences; extracting key feature vectors from the spatial feature vectors; establishing a distributed storage index database according to the key feature vectors of all video files in the video library; extracting key feature vector sets of videos to be retrieved and extracting video index files of the videos to be retrieved; performing the video similarity retrieving in the distributed storage index database according to the video index files of the videos to be retrieved and outputting video retrieval results of the video files with the similarity larger than the preset value of the system. Through the adoption of the method with the structure, representative visual words are adopted to replace key frames, video information is completely represented, a large amount of redundant of video information does not exist, the video information is very compact, the retrieval speed is increased, and the method has mass data concurrent processing capacity, and is wider in application range.

Description

technical field [0001] The invention relates to the technical field of multimedia information, in particular to the fields of multimedia information retrieval, data mining and video processing, and specifically refers to a method for realizing fast retrieval of massive videos. Background technique [0002] With the rapid development of multimedia information technology and the emergence of video sharing websites, the number of Internet videos has grown rapidly, and has increased exponentially. Publishing, sharing and retrieving videos through the Internet has become a way of life for people. In the face of massive multimedia data, how to quickly retrieve the same or similar videos has become a research hotspot in the industry and academia. [0003] Traditional video retrieval methods based on key frames are mainly inclined to the accuracy of video retrieval, but the computational complexity is extremely high, and it takes several minutes to complete a retrieval task. In th...

AI Technical Summary

Problems solved by technology

Retrieval videos and reference videos are often disturbed by various noises, such as video resolution degradation, network packet loss, video frame loss, low frame rate, video insertion, video editing, etc., which will make the original video information mixed with noise, or cause partial information to be lost and no longer complete

The traditional video key frame extraction method is too idealistic, a) the complexity of external interference is not considered, and appropriate redundancy is necessary, b) the features used to extract key frames are not constructed for massive retrieval tasks, related The method is not suitable for directly extracting keyframes

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