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A blink detection method based on an eye contour feature point aspect ratio

A contour feature and aspect ratio technology, applied in computer parts, instruments, biological neural network models, etc., can solve the problem of poor positioning effect of human eye edge detection, and achieve the effect of high precision, high efficiency and simple calculation

Inactive Publication Date: 2019-06-04
CHENGDU UNIV +1
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AI Technical Summary

Problems solved by technology

In low light, the positioning effect of ASM on the human eye and the edge detection effect of Canny on the human eye are not good.

Method used

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  • A blink detection method based on an eye contour feature point aspect ratio
  • A blink detection method based on an eye contour feature point aspect ratio
  • A blink detection method based on an eye contour feature point aspect ratio

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Embodiment Construction

[0024] In the following, the present invention will be further described in detail in conjunction with the accompanying drawings and embodiments, so as to make the purpose, technical solutions and advantages of the present invention more clear. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0025] figure 1 A blink detection method based on the aspect ratio of eye contour feature points according to an exemplary embodiment of the present invention is shown. The method of this embodiment mainly includes:

[0026] Step 101, obtaining video stream data, and extracting a single-frame human face image set from the video stream;

[0027] Specifically, the video stream data in the camera is obtained (when the blink detection, liveness detection or face verification is performed, the camera will be turned on, the corresponding video data will be collected, and in the correspond...

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Abstract

The invention discloses a blink detection method based on an eye contour feature point aspect ratio, and the method comprises the steps: obtaining a video stream, and extracting a single-frame face image set from the video stream; Extracting a face rectangular frame in the face image from the single-frame face image set by using a deep neural network, and obtaining a face rectangular frame coordinate; Obtaining eye key point coordinates in the single-frame face image set according to the face rectangular frame coordinates; Calculating the eye aspect ratio of the single-frame face image set according to the eye key point coordinates so as to judge whether blinking occurs or not according to the eye aspect ratio. According to the method, whether blinking occurs or not is judged by calculating the double-eye aspect ratio, the influence of light intensity, character postures and the like on blinking judgment can be overcome, high robustness is achieved, and the method is simple in calculation, high in precision, high in efficiency and capable of being better applied to the fields of living body recognition, fatigue driving monitoring and the like.

Description

technical field [0001] The invention relates to the technical fields of digital image processing and computer vision, in particular to a blink detection method based on the aspect ratio of eye contour feature points. Background technique [0002] At present, the field of security has attracted much attention, among which live body recognition and fatigue driving monitoring have attracted much attention. In terms of live body recognition and fatigue driving monitoring, the use of blink detection to realize their respective functions is now the mainstream, and it has the advantages of no cooperation and intelligentization. features. [0003] At present, there are many kinds of eye blink detection algorithms, but their accuracy rate needs to be improved. For example, based on Adaboost's blink detection, the Adaboost algorithm is an iterative algorithm, and its core idea is to train classifiers (weak classifiers) with different general classification capabilities for the same t...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/00G06N3/04
Inventor 余化鹏白儒谢浩常永鑫
Owner CHENGDU UNIV
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