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Human body motion feature extraction method based on global remarkable edge area

A technology of edge areas and human movements, applied in the field of video analysis, can solve problems such as spending a lot of time on labeling

Inactive Publication Date: 2016-05-04
WUHAN UNIV
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

The disadvantage of this method is that it takes a lot of time to label video samples with human experience, or rely on smart somatosensory devices to calibrate bone joint points

Method used

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  • Human body motion feature extraction method based on global remarkable edge area
  • Human body motion feature extraction method based on global remarkable edge area
  • Human body motion feature extraction method based on global remarkable edge area

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Embodiment Construction

[0059] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0060] see figure 1 , a method for extracting human motion features based on a global salient edge region provided by an embodiment of the present invention, specifically includes the following steps:

[0061] Step 1: Reduce the number of colors in the RGB color space and smooth the salience of the color space. The specific implementation process is: define the kth pixel I in the image I k The significance S(·) of is:

[0062] S ( I k ) = Σ ...

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Abstract

The invention discloses a human body motion feature extraction method based on a global remarkable edge area, comprising steps of using a contrast between an area and a whole image to calculate the significance, reducing the color quantity of the color space, smoothing the significance of the color space, calculating the significance area according to the space relation of the neighboring areas, performing morphology gradient changing on the foreground area segmented by a binarized threshold to generate a global remarkable edge area, traversing strong corner points of all grids of the video frames under various sizes, collecting key characteristic points, the light stream amplitude value of which is not 0, in the remarkable edge area, solving the displacement of the strong corner point according to the corrected light stream field, and forming the human body motion local time space characteristic by using the strong corner point continuous multi-frame displacement locus and the neighbourhood gradient vector. The invention extracts the motion characteristics through global remarkable edge area, eliminates the background noise points irrelevant to the human body motion, removes the affect on the light stream calculation by the camera motion, improves the accuracy of the human body motion local time space characteristic description and improves the human body motion recognition rate.

Description

technical field [0001] The invention belongs to the field of video analysis, and relates to a method for automatic recognition of human behavior, in particular to a method for extracting human motion features based on a global salient edge region. Background technique [0002] With the continuous development of the Internet and the continuous promotion of video surveillance systems, the amount of video data has increased dramatically. Facing the massive video data, how to analyze video human behavior has become an urgent problem to be solved. Because video data is easily affected by unclear foreground motion areas, large camera shakes, and complex scene environments, there are a large number of noise corners in human motion in video data, resulting in inaccurate extraction of key feature points in video frames, and human behavior recognition. Precision is limited. [0003] Human action feature extraction is an important part of human action recognition and belongs to an im...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06T7/00
CPCG06T2207/20036G06V40/20G06V10/44
Inventor 胡瑞敏徐增敏陈军陈华锋李红阳王中元郑淇吴华王晓周立国
Owner WUHAN UNIV
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