Face recognition working method through fusion of binary features and a joint laminated structure, and an intelligent chip

A face recognition, layered structure technology, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as a large amount of computational cost and storage cost, and the impossibility of model training.

Inactive Publication Date: 2019-03-19
CHONGQING VOCATIONAL INST OF ENG
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Problems solved by technology

However, at present, many supervised hashing methods usually use image pairs or image triplets for training, which requi

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  • Face recognition working method through fusion of binary features and a joint laminated structure, and an intelligent chip
  • Face recognition working method through fusion of binary features and a joint laminated structure, and an intelligent chip
  • Face recognition working method through fusion of binary features and a joint laminated structure, and an intelligent chip

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Embodiment Construction

[0098] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0099] Such as figure 1 with 2 As shown, the basic idea of ​​deep binary face hashing is to build a hash layer in the convolutional neural network, and learn its corresponding hash function while learning the feature representation, so that the extracted features are changed from floating-point features to Features converted to binary. The schematic diagram of deep binary face hashing is as follows figure 1As shown in , the activation value of the hash layer after the forward propagation of the network is the latent attribute, that is...

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Abstract

The invention provides a face recognition working method through fusion of binary features and a joint laminated structure and an intelligent chip. The method comprises the following steps: S1, acquiring face feature data in image features, and constructing a face feature data hash layer in a convolutional neural network, S2, enabling a face feature data hash function to meet the constraints of independence and minimum quantization error, and solving the face feature data hash function; S3, performing deep face feature data transformation on the solved face feature data hash function by usingcascade structure data operation; s4, through a depth binary human face feature data hash function, extracted human face feature data and human face feature data key point detection, human face feature data posture estimation and human face feature data classification are carried out; and S5, after face feature data mining, face image comparison and recognition are carried out by utilizing similarity, face feature data are identified and extracted, and required face feature data are obtained.

Description

technical field [0001] The invention relates to the field of computer control, in particular to a face recognition working method and an intelligent chip through the fusion of binary features and a joint stacked structure. Background technique [0002] In the research and application of existing face recognition algorithms, the similar proximity search technology used in face verification or face identification has become one of the important factors affecting the speed of the algorithm. How to further improve the speed of similar proximity search technology has become a research topic. top priority. [0003] Researchers have proposed two ideas to solve this problem. One is to use dimensionality reduction methods on the original feature representation to obtain shorter feature representations, such as the principal component analysis (Principal Component Analysis, PCA) method; the other is to use The feature representation is converted into a binary feature representation; ...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/1347G06V40/1365G06V10/955G06F18/2413G06F18/24147
Inventor 胡佩杨智勇
Owner CHONGQING VOCATIONAL INST OF ENG
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