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Human body behavior recognizing method based on RGB-D video

A recognition method and behavior technology, applied in the field of computer vision behavior recognition, can solve the problems of stability and low recognition accuracy, and achieve the effect of avoiding dimension disaster, improving accuracy and eliminating weakening influence

Active Publication Date: 2015-05-06
NANJING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

[0008] To sum up, the existing human behavior recognition technology based on RGB-D data generally has the problem of feature stability and low recognition accuracy.

Method used

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  • Human body behavior recognizing method based on RGB-D video
  • Human body behavior recognizing method based on RGB-D video
  • Human body behavior recognizing method based on RGB-D video

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Embodiment Construction

[0042] The technical scheme of the present invention is described in detail below in conjunction with accompanying drawing:

[0043] The idea of ​​the present invention is to extract dense MovingPose features, SHOPC features and HOG3D features from the RGB-D video acquired by the RGB-D camera, and use the MCMKL method to perform The fusion processing of the three features obtains the complementary information of the significant features in each feature. Finally, the Exemplars-SVM classifier is used to judge the human behavior category.

[0044] The human behavior recognition method based on RGB-D video of the present invention, comprises training phase and testing phase, and its overall process is as follows figure 1 shown.

[0045] The training phase includes the following steps:

[0046] Step A: Obtain RGB-D video samples of each human behavior class and remove redundant frames from each RGB-D video sample according to the motion energy of human skeleton nodes.

[0047] ...

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Abstract

The invention disclosers a human body behavior recognizing method based on an RGB-D video and belongs to the technical field of computer vision behavior recognition. The method includes extracting the dense Moving Pose feature, the SHOPC feature and the HOG3D feature from the RGB-D video acquired from an RGB-D camera according to the principle that human body behaviors of different classes in the RGB-D video have different moving information, geographic information and texture information, adopting an edge-limited multi-core learning method to conduct feature fusion on the three types of features, and finally adopting an Exemplars-SVM linear classifier is adopted to judge human body behavior action. Compared with the prior art, the three types of features extracted have the advantages of illumination invariance, scale invariance and view angle invariance, obvious robustness is achieved for the appearance difference and the behavior action process difference of action executers , and the human body behavior action recognition accuracy is improved to some extent.

Description

technical field [0001] The invention relates to a human behavior recognition method, in particular to a human behavior recognition method based on RGB-D video, and belongs to the technical field of computer vision behavior recognition. Background technique [0002] Human behavior recognition can be applied in many aspects, such as intelligent monitoring, human-computer interaction and sports video processing. Based on the input video data, human behavior recognition methods can be divided into three categories, including: methods based on RGB video data, methods based on depth video data, and methods based on the combination of the two data. [0003] Since depth sensors can acquire richer appearance and structural information, depth cameras have received more and more attention in the field of computer vision. In recent years, more and more companies have developed RGB-D cameras, which are characterized by the ability to provide RGB images and depth images in real time. For...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06T7/251G06T2207/10016G06T2207/30196G06V40/103G06F18/23213G06F18/2411
Inventor 陈克虎刘天亮
Owner NANJING UNIV OF POSTS & TELECOMM
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