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A sketch face recognition method based on depth transfer learning

A transfer learning, face recognition technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problem of image data not providing enough samples for training, overfitting, etc.

Inactive Publication Date: 2019-02-19
NANJING UNIV OF POSTS & TELECOMM
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  • Abstract
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Problems solved by technology

However, limited image data often cannot provide enough samples for training, which is easy to cause overfitting

Method used

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  • A sketch face recognition method based on depth transfer learning
  • A sketch face recognition method based on depth transfer learning
  • A sketch face recognition method based on depth transfer learning

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Embodiment Construction

[0060] The present invention will be further described below in conjunction with the accompanying drawings and specific examples. The following examples are only used to illustrate the technical solutions of the present invention more clearly, but not to limit the protection scope of the present invention.

[0061] The present invention provides a sketch face recognition method based on deep transfer learning. The present invention will be further described below in conjunction with the accompanying drawings and embodiments. First, establish a deep learning network for recognizing natural photos of human faces, and use the LFW library containing large-scale human face images for training to obtain an initial model that can obtain common features of human faces, such as figure 1 shown in [101]; then, using the transfer learning strategy, the initial model parameters are transferred to the deep learning network for face sketch images, such as figure 1 Shown in [105]; then pass ...

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Abstract

The invention discloses a sketch face recognition method based on depth transfer learning, comprising the following steps: step 1, establishing a depth convolution neural network model; 2, preprocessing images in a CUFSF sketch image library; 3, preprocessing that LFW image library containing large-scale natural face photograph, taking the LFW image library as an initial training sample to train anetwork, and obtaining a training model; 4, migrating that training model to a network for sketch face photographs to obtain a pre-training model; 5, establishing a three-tuple image composed of a reference image, a positive sample image and a negative sample image; 6, taking that triple image group as the input of the pre-training model, minimizing the los function by using the back propagationalgorithm, and performing training to obtain the final target training model; 7, testing that target training model obtain in the step 6 with a test set to carry out face recognition of a sketch image. This method has the advantage of high recognition accuracy of sketch face image.

Description

technical field [0001] The invention relates to the technical fields of image recognition and deep learning, and relates to a sketch face recognition method based on deep transfer learning. Background technique [0002] An important application of face recognition is to assist law enforcement. Realizing the automatic retrieval of the facial photo database of the Ministry of Public Security can quickly narrow down the range of suspects. In most cases, however, photos of suspects are not available. In situations where there is no surveillance or the surveillance footage is not clear, the best alternative is a sketch drawn by a portrait expert based on eyewitness descriptions. Therefore, a sketch is used to automatically match individuals in a photo database. However, the details of the face in the suspect's sketch are often inaccurate, the relative position of facial features is not reliable, and the features may be exaggerated. Therefore, the main challenge of face recogn...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/172G06F18/22G06F18/241G06F18/214
Inventor 宋建新王欣欣
Owner NANJING UNIV OF POSTS & TELECOMM
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