Living body recognition method based on facial feature point motion

Yulong WANG; Kaiyuan LIU

doi:10.11959/j.issn.2096-109x.2018044

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Living body recognition method based on facial feature point motion

Papers | 更新时间：2024-06-03

- Living body recognition method based on facial feature point motion
- Chinese Journal of Network and Information Security Vol. 4, Issue 6, Pages: 36-44(2018)
- 作者机构：
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- 基金信息：
- DOI：10.11959/j.issn.2096-109x.2018044
  CLC： TP301.6
- Online First：2018-06，
  
  Published：15 June 2018
- 稿件说明：
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Yulong WANG, Kaiyuan LIU. Living body recognition method based on facial feature point motion[J]. Chinese Journal of Network and Information Security, 2018, 4(6): 36-44.
DOI：

Yulong WANG, Kaiyuan LIU. Living body recognition method based on facial feature point motion[J]. Chinese Journal of Network and Information Security, 2018, 4(6): 36-44. DOI： 10.11959/j.issn.2096-109x.2018044.

摘要

提出一种应用于手机移动端基于深度学习反照片及反视频的生物识别方法，该方法利用面部动作数据集训练一个LSTM网络，通过用户配合输入一段随机动作顺序的视频，对视频预处理后提取面目特征特点得到特征点数据，最后将特征点数据放入循环神经网络判断视频是否发生了伪造攻击。实验结果表明，该方法能够有效抵御照片攻击和视频回放攻击。

Abstract

A kind of living body recognition method was proposed

which was applied in mobile terminal and based on the deep learning.A facial movements LSTM network was trained using data sets.When users input a random sequence of video

user’s facial feature point data can be gained and whether the video forgery attacks happened will be determined by input user’s facial feature point data into circulation neural network.The test data shows that the proposed method can be protected effectively from photograph attack and video replay attack.

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references

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