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Face quality evaluation method and system based on random embedding stability

A technology for quality evaluation and stability, applied in the field of face recognition and evaluation, it can solve the problems of inaccurate manual annotation and unclear annotation standards, and achieve the effect of saving computing time.

Pending Publication Date: 2021-08-13
北京睿芯高通量科技有限公司
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Problems solved by technology

[0005] In order to solve the above problems, the present invention provides a face quality evaluation method and system based on random embedding stability, which is used to cover interference factors such as occlusion, posture, illumination, resolution, and ambiguity to obtain stable and reliable face quality evaluation scores, and there is no need to construct a training set that requires manual labeling, avoiding the problems of inaccurate manual labeling and unclear labeling standards

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  • Face quality evaluation method and system based on random embedding stability
  • Face quality evaluation method and system based on random embedding stability
  • Face quality evaluation method and system based on random embedding stability

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Embodiment 1

[0044] figure 2 It is a flow chart of the human face quality evaluation method in an embodiment of the present invention, as figure 2 As shown, the present embodiment provides a face quality evaluation method based on random embedding stability, which is embedded in the face recognition neural network, and the face quality evaluation score is obtained while performing the face recognition process, specifically Include the following steps:

[0045] Step 1: Obtain the video stream collected by the surveillance camera, and extract frames for each image frame in the video stream according to preset rules;

[0046] In this embodiment, the frame drawing rule adopted in step 1 is specifically to extract one frame for every 10 frames of images. In other embodiments, other numbers of frame drawing intervals can also be used for frame drawing. The present invention does not apply to frame drawing intervals are limited.

[0047] Step 2: Carry out face detection to any image frame ex...

Embodiment 2

[0062] Figure 4 It is a framework diagram of a human face quality evaluation system according to an embodiment of the present invention, as Figure 4 As shown, the present embodiment provides a face quality evaluation system based on random embedding stability, which is embedded in the face recognition neural network, and is used to obtain the face quality evaluation score while performing the face recognition process. include:

[0063]The video image preprocessing module (401), is used for preprocessing the input video stream, and the preprocessing includes extracting image frames from the video stream, performing face detection on the extracted image frames, and cutting and aligning the detected people ;

[0064] The first neural network module (402), is connected with the video image preprocessing module (401), and is used for extracting facial feature;

[0065] The second neural network module (403), connected with the first neural network module (402), is used to calc...

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Abstract

The invention discloses a face quality evaluation method and system based on random embedding stability, and the method comprises the steps: carrying out the embedding in a face recognition neural network, obtaining a face quality evaluation score during the face recognition process, and specifically includes: 1, carrying out the frame extraction of each image frame in a video stream according to a preset rule; 2, performing face detection on any image frame, and performing cutting alignment on the detected face to obtain a face image; 3, inputting the face image into a first neural network to obtain a corresponding face feature; 4, inputting the face features into a second neural network to obtain n random features; 5, combining the n random features in pairs to obtain different random feature pairs, and calculating a face quality evaluation score according to the feature pairs; and 6, inputting the face features in the step 3 into a third neural network to obtain face recognition features for a subsequent face recognition or comparison process.

Description

technical field [0001] The invention relates to the field of face recognition and evaluation, in particular to a face quality evaluation method and system based on random embedding stability. Background technique [0002] Face recognition technology is one of the important contents in the field of security monitoring. figure 1 It is the architecture diagram of the existing face recognition system, such as figure 1 As shown, in general, a face recognition system is mainly composed of four parts: face detection, face alignment, face quality evaluation and face recognition. Face quality evaluation is one of the important components in the face recognition system. It is used to evaluate the imaging quality of a face image and whether the image can be used for face recognition. Its significance lies in: 1) low-quality faces The image will reduce the recognition rate and reliability of the face recognition system. The face recognition system will be interfered by factors such as...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06T3/00G06N3/04G06N3/08
CPCG06N3/08G06V40/168G06V20/46G06N3/045G06F18/214G06T3/147Y02P90/30
Inventor 李阳罗鑫
Owner 北京睿芯高通量科技有限公司
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