Systems and methods for anti-spoofing protection using multi-frame feature point analysis

A system, comprising:

• a memory storing instructions;
• a processor coupled to the memory and configured by the instructions to at least:
• capture a live video of a user;
• for a first frame of the live video:
• identify a first facial region of the user;
• determine a first plurality of regions of interest within the first facial region;
• and
• identify a plurality of feature points for each of the first plurality of regions of interest;
• for a second frame of the live video:
• identify a second facial region of the user;
• determine a second plurality of regions of interest within the second facial region;
• and
• identify a plurality of feature points for each of the second plurality of regions of interest, wherein locations of the feature points in the second plurality of regions of interest in the second frame coincide with locations of the feature points in the first plurality of regions of interest in the first frame;
• generate a perspective transform matrix based on locations of the feature points in the second plurality of regions of interest in the second frame and locations of the feature points in the first plurality of regions of interest in the first frame to generate transformed coordinates of a plurality of first background feature points;
• determine a difference value between coordinates of a plurality of second background feature points and the transformed coordinates of the plurality of first background feature points;
• and
• determine whether the user is spoofing the system based on the difference value.

A non-transitory computer-readable storage medium storing instructions to be implemented by a computing device having a processor, wherein the instructions, when executed by the processor, cause the computing device to at least:

• capture a live video of a user;
• for a first frame of the live video:
• identify a first facial region of the user;
• determine a first plurality of regions of interest within the first facial region;
• and
• identify a plurality of feature points for each of the first plurality of regions of interest;
• for a second frame of the live video:
• identify a second facial region of the user;
• determine a second plurality of regions of interest within the second facial region;
• and
• identify a plurality of feature points for each of the second plurality of regions of interest, wherein locations of the feature points in the second plurality of regions of interest in the second frame coincide with locations of the feature points in the first plurality of regions of interest in the first frame;
• generate a perspective transform matrix based on locations of the feature points in the second plurality of regions of interest in the second frame and locations of the feature points in the first plurality of regions of interest in the first frame to generate transformed coordinates of a plurality of first background feature points;
• determine a difference value between coordinates of a plurality of second background feature points and the transformed coordinates of the plurality of first background feature points;
• and
• determine whether the user is spoofing the computing device based on the difference value.