Spoof detection using head pose to eye gaze correspondence

A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising:

• providing, by a processor of a user device having a camera, instructions on a display panel of the user device, the instructions provided for performing a head movement;
• capturing a set of images of a subject using the camera of the user device subsequent to providing the instructions to perform the head movement;
• determining, by the processor from the set of images, a first metric indicative of an amount of change in eye gaze directions of the subject during the head movement;
• determining, by the processor from the set of images, a second metric indicative of a change in head positions of the subject during the head movement;
• determining, by the processor based at least on the first metric and the second metric, a third metric indicative of a likelihood that the subject is a live person, wherein the third metric is a weighted sum of (i) the second metric and (ii) an inverse of the first metric;
• determining that the third metric satisfies a first threshold condition;
• and
• in response to determining that the third metric satisfies the first threshold condition, identifying the subject as a live person.

A computer-implemented system comprising:

• one or more computers;
• and
• one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform operations comprising:
• providing, by a processor of a user device having a camera, instructions on a display panel of the user device, the instructions provided for performing a head movement;
• capturing a set of images of a subject using the camera of the user device subsequent to providing the instructions to perform the head movement;
• determining, by the processor from the set of images, a first metric indicative of an amount of change in eye gaze directions of the subject during the head movement;
• determining, by the processor from the set of images, a second metric indicative of a change in head positions of the subject during the head movement;
• determining, by the processor based at least on the first metric and the second metric, a third metric indicative of a likelihood that the subject is a live person, wherein the third metric is a weighted sum of (i) the second metric and (ii) an inverse of the first metric;
• determining that the third metric satisfies a first threshold condition;
• and
• in response to determining that the third metric satisfies the first threshold condition, identifying the subject as a live person.