Face verification method and apparatus
Disclosed is a face verification method and apparatus. The method including analyzing a current frame of a verification image, determining a current frame state score of the verification image indicating whether the current frame is in a state predetermined as being appropriate for verification, determining whether the current frame state score satisfies a predetermined validity condition, and selectively, based on a result of the determining of whether the current frame state score satisfies the predetermined validity condition, extracting a feature from the current frame and performing verification by comparing a determined similarity between the extracted feature and a registered feature to a set verification threshold.
1. A mobile device, comprising:
one or more processors configured to:
obtain an image for a user;
ascertain a sleep state of the user based on the obtained image;
select to not perform a user verification when the sleep state of the user is ascertained; and
unlock the mobile device, to permit the user to access functions of the mobile device, when the user verification verifies the user.
2. The mobile device of claim 1 , wherein the one or more processors are further configured to ascertain the sleep state of the user according to whether eyes of the user are closed.
3. The mobile device of claim 1 , wherein the one or more processors are further configured to ascertain the sleep state of the user according to a number of frames of the image in which eye closure of the user is detected.
4. The mobile device of claim 1 , wherein the one or more processors are further configured to output a message indicating the ascertained sleep state of the user.
5. The mobile device of claim 1 , further comprising a memory storing instructions that configure the at least one processor to perform the user verification, including implementation of a machine learning verification model with respect to the image.
6. The mobile device of claim 5 , wherein the machine learning verification model includes a neural network.
7. The mobile device of claim 5 , wherein the one or more processors are further configured to determine a result of the performed user verification through consideration of a similarity, with respect to registered verification information and a result of the implementation of the machine learning verification model.
8. A processor-implemented method of a device, comprising:
obtaining an image for a user;
ascertaining a sleep state of the user based on the obtained image;
selecting to not perform a user verification when the sleep state of the user is ascertained; and
unlocking the mobile device, to permit the user to access functions of the mobile device, when the user verification verifies the user.
9. The method of claim 8 , wherein the ascertaining comprises ascertaining the sleep state of the user according to whether eyes of the user are closed.
10. The method of claim 8 , wherein the ascertaining comprises ascertaining the sleep state of the user according to a number of frames of the image in which eye closure of the user is detected.
11. The method of claim 8 , further comprising outputting a message indicating the ascertained sleep state of the user.
12. The method of claim 8 , further comprising performing the user verification, including implementation of a machine learning verification model with respect to the image.
13. The method of claim 12 , wherein the machine learning verification model includes a neural network.
14. The method of claim 12 , further comprising determining a result of the performed user verification through consideration of a similarity, with respect to registered verification information and a result of the implementation of the machine learning verification model.
15. A mobile device, comprising:
a camera configured to generate an image for a user; and
one or more processors configured to:
ascertain a sleep state of the user based on the generated image;
select to not perform a user verification when the sleep state of the user is ascertained; and
unlock the mobile device, to permit the user to access functions of the mobile device, when the user verification verifies the user, wherein the user verification is based on a machine learning verification model.
16. The mobile device of claim 15 , wherein the one or more processors are further configured to ascertain the sleep state of the user according to whether eyes of the user are closed.
17. The mobile device of claim 15 , wherein the one or more processors are further configured to ascertain the sleep state of the user according to a number of frames of the image in which eye closure of the user is detected.
18. The mobile device of claim 15 , wherein the one or more processors are further configured to output a message indicating the ascertained sleep state of the user.
19. The mobile device of claim 15 , wherein the machine learning verification model includes a neural network.
20. The mobile device of claim 15 , wherein the one or more processors are further configured to determine a result of the performed user verification through consideration of a similarity, with respect to registered verification information and a result of the implementation of the machine learning verification model.