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Human face model matrix training method and device

A face model and training method technology, applied in the computer field, can solve problems such as memory space consumption, and achieve the effect of reducing memory and computing complexity

Active Publication Date: 2019-04-23
TENCENT TECH (SHENZHEN) CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] In the process of implementing the present invention, the inventor found at least the following problems in the prior art: the terminal needs to simultaneously load all face images in the face image library to the memory, consuming a large amount of memory space

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  • Human face model matrix training method and device
  • Human face model matrix training method and device

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Embodiment Construction

[0022] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments . Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0023] The face model matrix training methods involved in various embodiments of the present invention can be used in the server 100 . Specifically, please refer to figure 1 , the server 100 includes a central processing unit (CPU) 101, a system memory 104 including a random access memory (RAM) 102 and a read only memory (ROM) 103, and a system bus 105 connecting the system memory 104 and the central processing unit 101 . The server 100 ...

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Abstract

The invention discloses a human face model matrix training method and device, belonging to the technical field of computers. The method includes: obtaining a face image library, the face image library includes k groups of face images, each group of face images includes at least one face image of at least one person, k>2; for the k groups Each group of face images in the face images is analyzed respectively, and the first matrix and the second matrix are calculated according to the analysis results; the first matrix is ​​the intragroup covariance matrix of the face features of each group of face images, so The second matrix is ​​the inter-group covariance matrix of the face features of the k groups of face images; according to the first matrix and the second matrix, the face model matrix is ​​trained. It avoids the problem that the terminal takes up a lot of memory when loading all the face images in the face image library to the memory at the same time in the prior art, and can only load the face images in one group to the memory at a time, thereby reducing the training process. The effect of the memory required in the .

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a face model matrix training method and device. Background technique [0002] Facial recognition technology usually consists of two steps. First, feature extraction is performed on the target face image; second, similarity calculation is performed between the extracted features and the features in the reference face image. [0003] Before calculating the similarity, the terminal needs to calculate the face model matrix based on each face image in the face image library, and then calculate the similarity between the extracted features and the features in the reference face image based on the calculated face model matrix . In the prior art, the terminal needs to calculate all the face images in the face image database at the same time, and train the face model matrix according to the calculation results. [0004] In the process of implementing the present invention, the invent...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
CPCG06V40/169G06V40/172G06V10/761G06F18/00G06F18/22G06F18/213G06T2207/30201G06T2207/20081G06V40/16G06V10/469G06V20/653G06F17/16G06V40/161
Inventor 丁守鸿李季檩汪铖杰黄飞跃吴永坚谭国富
Owner TENCENT TECH (SHENZHEN) CO LTD