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Human body motion video recognition method based on non-negative matrix factorization

A technology of non-negative matrix decomposition and human motion, applied in the field of image processing, can solve problems such as poor applicability, high feature dimension, and large amount of calculation, and achieve the effect of improving recognition rate, strong applicability, and reducing dimension

Inactive Publication Date: 2014-07-02
XIDIAN UNIV
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Problems solved by technology

Although this method achieves a high recognition rate at different viewing angles, there are still shortcomings: the feature dimension is high, the amount of calculation is large, it is easily affected by changes in external lighting, and the applicability is not strong.

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  • Human body motion video recognition method based on non-negative matrix factorization
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  • Human body motion video recognition method based on non-negative matrix factorization

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Embodiment Construction

[0045]The present invention will be further described below in conjunction with the accompanying drawings.

[0046] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0047] Step 1, preprocessing video images.

[0048] In the first step, 90 human body action video images are input. Among the input human body action video images, 80 human body action video images are selected as a human body action video training sample set, and the remaining 10 human body action video images are each used as a human body action video image. Action video training sample set.

[0049] The human action video images used come from the Weizmann human action recognition database, and the download address is: http: / / www.wisdom.weizmann.ac.il / ~vision / SpaceTimeActions.html. The database contains a total of 90 videos of 9 people performing 10 different actions.

[0050] The second step is to convert the human action video images in the human action video...

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Abstract

The invention discloses a human body motion video recognition method based on non-negative matrix factorization. The human body motion video recognition solves the problems that due to the fact that in the prior art, extraction of characteristics of a motion vehicle is influenced by the background environment, the recognition rate is lowered, and due to the fact that the number of the dimensions of the extracted characteristics is excessively high, the calculation amount is excessively large. The method specifically includes the steps of firstly, preprocessing a data set; secondly, detecting space interest points; thirdly, constructing a cube; fourthly, constructing a characteristic matrix; fifthly, training a dictionary; sixthly, conducting classification. According to the method, the influences of the background environment on characteristic extraction can be effectively eliminated in the human body motion video recognition process, the recognition rate of the human body motion video can be improved, the number of the dimensions of the extracted characteristics is low, and the calculation amount and the complexity in the human body motion video recognition process are reduced.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a human action video recognition method based on non-negative matrix decomposition in video images. The invention can be used for intelligent monitoring, video retrieval, human-computer interaction, entertainment and sports analysis, etc. Background technique [0002] The purpose of human action video recognition is to automatically identify the type of human action video by analyzing the obtained human action video feature parameters on the basis of successful action tracking and feature extraction. Human action video recognition technology has broad application prospects in visual supervision, human-computer interaction, video conferencing, virtual reality and other fields. [0003] At present, many action video recognition techniques have been proposed, especially the methods based on the overall motion feature are widely used at present. It separates the huma...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/54
Inventor 韩红曹赛洪汉梯李楠陈建史媛媛
Owner XIDIAN UNIV
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