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High-dimensional multimedia data classifying method based on maximum margin tensor study

A multimedia data and maximum interval technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc. Multimedia data internal structure information and other issues

Active Publication Date: 2013-12-25
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

Because traditional classification methods often simply combine the extracted features, resulting in very high-dimensional data, resulting in a "dimension disaster" in data analysis
In addition, traditional methods do not consider the internal structure information existing in multimedia data, so they cannot process and analyze massive high-dimensional multimedia data well, and thus cannot well adapt to user needs

Method used

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  • High-dimensional multimedia data classifying method based on maximum margin tensor study
  • High-dimensional multimedia data classifying method based on maximum margin tensor study
  • High-dimensional multimedia data classifying method based on maximum margin tensor study

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Embodiment

[0124] Assuming the classification problem of action data, the action data has important structural information. Write a crawler program to download 50,000 action data in the relevant data set for training. Assume that there are 49 classes, extract the coordinates in the three directions of x, y, and z as its three features, and form the training tensor X∈R 3×49×50000 .

[0125] Model the training data set, analyze it, and obtain the classification model. The steps are as follows:

[0126] 1) According to the training tensor X, the objective function of the high-dimensional multimedia data classification based on the maximum interval tensor learning is obtained:

[0127] min U 1 , . . . U N | | X - C ...

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Abstract

The invention discloses a high-dimensional multimedia data classifying method based on maximum margin tensor study. The method includes the following steps that (1) a training data set of multimedia data is built; (2) the training data set is modeled and analyzed to obtain a classifying model; (3) according to a user inquiry data set and the classifying model, the inquiry data set is classified. According to high-dimensional performance and structure performance of the multimedia, the multimedia data is expressed through tensor, and high-dimensional multimedia data is classified through a maximum margin classifier method. Classifying is finished while the multimedia data is subjected to decomposition analysis, structural information in the multimedia data is reserved, dimensionality curse caused by high-dimensional data generated through a traditional splicing method is avoided, and the method is more accurate than a traditional multimedia data classifying method and facilitates calculation.

Description

technical field [0001] The invention relates to multimedia classification, in particular to a high-dimensional multimedia data classification method based on maximum interval tensor learning. Background technique [0002] With the development of computer storage technology and network technology, information is no longer just a single text or language, but presented in a more diverse form of multimedia, including text, pictures, sound, video, such as image database Picasa, video database YouTube Wait. How to effectively acquire, manage and utilize these multimedia data has become an increasingly important research problem in computer application technology. Multimedia classification technology can help users effectively query and manage these massive multimedia data. In general, multimedia data has two characteristics. First, high-dimensionality, multimedia data usually has a huge amount of data and high feature dimension; second, structural: multimedia data has internal ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 张寅汤斯亮谭谞邵健吴飞庄越挺
Owner ZHEJIANG UNIV
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