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liveness check
相关语句
  活性判别
     Liveness Check Algorithm Based on Eye Movement Model Using SVM
     基于支持向量机眼动模型的活性判别算法
短句来源
     Liveness check algorithm based on body temperature measurement model using SVM
     基于支持向量机体温检测模型的活性判别算法
短句来源
     We solved the liveness check problem using a Support Vector Machine based eye movement model We trained the eye movement model using many eye state examples And In the liveness check procedure, the user has to blink his/her eyes to get through the check The photos, which can not blink, are successfully stopped before entering the recognition stage
     提出一种基于支持向量机眼动模型的活性判别算法 该算法通过大量的人眼的样本来训练基于支持向量机的眼动模型 ,然后在活性判别过程中 ,通过被识别人进行眨眼的配合动作来完成活性判别的过程 由于人脸照片不可能做出眨眼的配合动作 ,因此照片就被成功地排除在了人脸识别系统的外面 ,从而提高了人脸自动识别系统的安全性
短句来源
     A liveness check algorithm based on body temperature measurement model using SVM(support vector machine) is proposed.
     提出了一种基于支持向量机体温检测模型的活性判别算法。
短句来源
     That raised the securities of face automatic recognition system. And in the liveness check procedure,the users do not need to do the change of the expression or the posture cooperates with recognition. The users use this system conveniently,and the conveniences of face recognition systems is strengthened.
     由于人脸照片的温度不可能与正常人的体温相同,所以照片就被成功的排除在了人脸识别系统的外面,从而提高了人脸自动识别系统的安全性,而且在活性判别过程中,被识别人不需要做表情或者是姿态的变化来配合识别,极大的方便了被识别者,增强了人脸识别系统的方便性。
短句来源
  相似匹配句对
     On Editing Check
     略论编辑把关
短句来源
     Woman check
     不孕女性应作哪些检查
短句来源
     Liveness Check Algorithm Based on Eye Movement Model Using SVM
     基于支持向量机眼动模型的活性判别算法
短句来源
     Liveness check algorithm based on body temperature measurement model using SVM
     基于支持向量机体温检测模型的活性判别算法
短句来源
     Analysis on the Liveness of S-net
     S-网的活性分析
短句来源
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  liveness check
When a quorum of backup replicas run the acknowledgment operation, the liveness check is complete.
      
Periodically, the backup group checks the liveness of the primary group, and transfers a snapshot of the service state as part of the liveness check.
      
It could also happen that the liveness check fails because the backup does not execute enough takeover operations.
      


We solved the liveness check problem using a Support Vector Machine based eye movement model We trained the eye movement model using many eye state examples And In the liveness check procedure, the user has to blink his/her eyes to get through the check The photos, which can not blink, are successfully stopped before entering the recognition stage

提出一种基于支持向量机眼动模型的活性判别算法 该算法通过大量的人眼的样本来训练基于支持向量机的眼动模型 ,然后在活性判别过程中 ,通过被识别人进行眨眼的配合动作来完成活性判别的过程 由于人脸照片不可能做出眨眼的配合动作 ,因此照片就被成功地排除在了人脸识别系统的外面 ,从而提高了人脸自动识别系统的安全性

A liveness check algorithm based on body temperature measurement model using SVM(support vector machine) is proposed.The body temperature measurement model is trained by a large number of examples with forehead and oxter temperatures.And in the liveness check procedure,the users' body temperature is measured to get through the liveness check.Because the temperature of face photos can not be the same as the body temperature of the normal person,the photos are successfully stopped before entering...

A liveness check algorithm based on body temperature measurement model using SVM(support vector machine) is proposed.The body temperature measurement model is trained by a large number of examples with forehead and oxter temperatures.And in the liveness check procedure,the users' body temperature is measured to get through the liveness check.Because the temperature of face photos can not be the same as the body temperature of the normal person,the photos are successfully stopped before entering the face recognition stage.That raised the securities of face automatic recognition system.And in the liveness check procedure,the users do not need to do the change of the expression or the posture cooperates with recognition.The users use this system conveniently,and the conveniences of face recognition systems is strengthened.

提出了一种基于支持向量机体温检测模型的活性判别算法。该算法通过大量的人体前额和腋下温度的样本来训练基于支持向量机的体温检测模型,然后在活性判别过程中,通过检测被识别人的体温来完成活性判别的过程。由于人脸照片的温度不可能与正常人的体温相同,所以照片就被成功的排除在了人脸识别系统的外面,从而提高了人脸自动识别系统的安全性,而且在活性判别过程中,被识别人不需要做表情或者是姿态的变化来配合识别,极大的方便了被识别者,增强了人脸识别系统的方便性。

 
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