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Method for video semantic mining

A semantic mining and video technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of high error rate of video content labeling, no comprehensive consideration of effective integration, lack of description information, etc.

Inactive Publication Date: 2011-10-19
NORTH CHINA UNIVERSITY OF TECHNOLOGY
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AI Technical Summary

Problems solved by technology

Because video is unformatted data and lacks necessary descriptive information, it cannot be processed as easily as text
Manual semantic annotation of videos is time-consuming and labor-intensive, and cannot meet the requirements of batch video processing
Content-based video processing technology is a current research hotspot, but the existing technology has a high error rate for video content labeling, and does not comprehensively consider the effective integration of image, text and voice content

Method used

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Embodiment Construction

[0018] Various details involved in the technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings. It should be pointed out that the described embodiments are only intended to facilitate the understanding of the present invention, rather than limiting it in any way.

[0019] The present invention proposes a method for video semantic mining, such as figure 1 As shown, the method is divided into four layers in the processing flow. The bottom layer is the video library layer, which stores various forms of video resources; the upper layer of the video library is the multi-modal fusion layer, where the structural analysis of the video and the recognition and effective fusion of images, text, and voice are completed; The next upper layer is the video mining layer, which realizes the graphical model representation of video and the video mining algorithm based on dense subgraph discovery. In addition, video classificati...

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Abstract

The invention relates to a method for video semantic mining, comprising the steps of: firstly performing a Chinese continuous speech recognition, a video target recognition and a video character recognition on a to-be-processed video; then performing a Chinese word division and a part-of-speech tagging on the recognition result, reserving nouns and verbs as the peaks of a graph model, wherein a side weight between the peaks is set to be the Chinese semantic distance of words represented by the two peaks; and finally mining the semantic information of the video according to a dense subgraph finding algorithm. The semantic mining of the video is realized by the fusion of the three recognition results of the Chinese continuous speech recognition, the video target recognition and the video character recognition; the video is represented to be a graph model, wherein the peaks are the words in the video, and the side weight is set to be the semantic distance between the two peaks; the video semantic mining algorithm is further transformed to be the dense subgraph finding algorithm of the graph model. The method and the device in the invention solve the problems of high error rate of a single recognition result and incapability of efficiently fusing a plurality of recognition results in the process of the Chinese continuous speech recognition, the video target recognition and the video character recognition, as well as solve the problem of the video structured expression and the problem of the video semantic mining algorithm realization. The method and the device in the invention can be used for performing automatic marking, classification and semantic mining on batches of videos.

Description

technical field [0001] The invention relates to the fields of digital media and machine learning. It performs semantic analysis on video input by users, and performs semantic annotation on the video by fusing voice, text and image information. Background technique [0002] With the development of online video sharing sites and video processing technology, a large number of content in video formats has emerged. Because video is unformatted data and lacks necessary descriptive information, it cannot be processed as easily as text. Manual semantic annotation of videos is time-consuming and labor-intensive, and cannot meet the requirements of batch video processing. Content-based video processing technology is a current research hotspot, but the existing technology has a high error rate for video content labeling, and does not comprehensively consider the effective integration of image, text and voice content. At present, the image target recognition technology is gradually ma...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 张师林
Owner NORTH CHINA UNIVERSITY OF TECHNOLOGY
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