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Human body behavior identification method based on depth sequence

A recognition method and sequence technology, applied in the field of pattern recognition and computer vision, can solve problems such as unsatisfactory effects, achieve the effect of filtering the background, strong robustness, and reduce the amount of data

Active Publication Date: 2016-07-06
BEIJING UNIV OF TECH
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  • Application Information

AI Technical Summary

Problems solved by technology

Existing studies have applied it to depth data, but the results achieved are not very satisfactory.

Method used

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  • Human body behavior identification method based on depth sequence
  • Human body behavior identification method based on depth sequence
  • Human body behavior identification method based on depth sequence

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Embodiment Construction

[0042] According to the description of the method above, the experimental verification was carried out. The experimental data chooses MSRAction3D database and MSRGesture3D database. The MSRAction3D database is a public database collected using the Microsoft Kinect depth sensor. The database consists of 10 performers completing 20 depth sequences of actions. Each action of each performer is collected 2-3 times, although the background of this database has been processed. , but because many of the 20 actions are very similar, it is still very challenging to recognize this data set; MSRGesture3D is a gesture database that acquires depth sequences through depth cameras, and is also a very popular human gesture test evaluation database . The database contains 12 dynamic gestures defined by AmericanSignLanguage (ASL). Each gesture was performed 2-3 times by 10 people. This database is quite challenging due to the self-occlusion problem.

[0043] The experimental results of the m...

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Abstract

The invention discloses a human body behavior identification method based on a depth sequence. The human body behavior identification method comprises the following steps: adopting a LBP (Local Binary Patterns) operator based on normal information; adopting a combined LBP operator of a spatial pyramid form; carrying out the sparse representation of the combined LBP operator; and carrying out the segmentation and the alignment of a behavior sequence. In order to obtain surface features which reflect different human body behavior surfaces in a depth map and further improve the robustness of human body behavior identification, a LBP description operator of normal information in the depth map is defined according to the similarity and the associated information of a human body structure in the depth map, wherein the operator keeps the geometric characteristics of a human body behavior surface on an aspect of details, extracts the local features of the surface on a local space, and expresses the local features as the human body behavior local features in the depth map. On the whole, detail information is integrated by a coding method based on dictionary learning, the local spatial structure relationship of a human body surface is kept by the pooling processing of an adaptive space-time pyramid and a thinning coefficient, and the detail and integral feature description of three-dimensional human body behaviors is realized.

Description

technical field [0001] The invention relates to the fields of pattern recognition and computer vision, in particular to a human behavior recognition method based on improved local binary patterns (LBP) and sparse representation. Background technique [0002] Human behavior recognition has been widely used in video surveillance, medical and health care and other fields. However, the current research on human behavior recognition mainly focuses on the traditional color image video. Because the color image video lacks the three-dimensional space information of the human body, the description of behavior characteristics is not comprehensive enough, and it is difficult to deal with the feature description of occlusion, illumination and behavior appearance changes. Therefore, its application effect and scope have certain limitations. With the advancement of image acquisition technology, depth image acquisition is getting easier and easier. Compared with traditional color images,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V40/20
Inventor 孙艳丰张坤胡永利
Owner BEIJING UNIV OF TECH
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