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Training method of posture recognition model and image recognition method and device

A technology for recognizing models and gestures, applied in the field of machine learning, can solve the problems of low training efficiency, large amount of computing resources, and incompatibility of neural network models, and achieve the effect of high training efficiency, simple model and high accuracy

Active Publication Date: 2019-07-16
TENCENT TECH (SHENZHEN) CO LTD
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Problems solved by technology

[0003] In related technologies, the neural network models used to recognize two-dimensional posture information and three-dimensional posture information of the human body are incompatible with each other and need to be trained separately, which requires a large amount of computing resources and low training efficiency

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  • Training method of posture recognition model and image recognition method and device
  • Training method of posture recognition model and image recognition method and device
  • Training method of posture recognition model and image recognition method and device

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Embodiment Construction

[0081] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with the accompanying drawings, and the described embodiments should not be considered as limiting the present invention, and those of ordinary skill in the art do not make any All other embodiments obtained under the premise of creative labor belong to the protection scope of the present invention.

[0082] In the following description, references to "some embodiments" describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or a different subset of all possible embodiments, and Can be combined with each other without conflict.

[0083] In the following description, the terms "first\second" are only used to distinguish similar objects, and do not represent a specific order for objects. Understandably, "first\second" can be The particular...

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Abstract

The invention provides a training method of a posture recognition model and an image recognition method and device. The training method of the posture recognition model comprises: inputting a sample image marked with human body key points into a feature map model included in the posture recognition model, and outputting a feature map corresponding to the sample image; inputting the feature map into a two-dimensional model included in the posture recognition model, and outputting two-dimensional key point parameters for representing a two-dimensional human body posture; inputting a target humanbody feature map cut from the feature map and the two-dimensional key point information into a three-dimensional model included in the posture recognition model, and outputting three-dimensional posture parameters for representing a three-dimensional human body posture; constructing a target loss function by combining the two-dimensional key point parameters and the three-dimensional attitude parameters; and based on the target loss function, updating model parameters of the attitude recognition model.

Description

technical field [0001] The invention relates to the technical field of machine learning, in particular to a training method for a posture recognition model, an image recognition method and a device. Background technique [0002] Machine learning (ML, machine Learning) is a branch of artificial intelligence, its purpose is to let the machine learn based on prior knowledge, so as to have the logical ability of classification and judgment. The machine learning model represented by neural network continues to develop and is gradually applied to human body posture recognition, so as to realize various intelligent applications based on human body posture. [0003] In related technologies, the neural network models used to recognize two-dimensional posture information and three-dimensional posture information of the human body are incompatible with each other and need to be trained separately, which requires a large amount of computing resources and low training efficiency. Conte...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/08G06V10/764
CPCG06N3/084G06V40/10G06F18/214G06V40/23G06V40/103G06T7/75G06T2207/20081G06T2207/20084G06T2207/30196G06V10/764G06N3/045G06T7/74G06V20/647
Inventor 罗镜民朱晓龙王一同季兴
Owner TENCENT TECH (SHENZHEN) CO LTD
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