Methods and systems for enhancing user liveness detection

1. A method for enhancing user liveness detection comprising:

capturing, by a camera included in a computing device, facial images of a user in a video;

calculating, by the computing device, parameters for frames included in the video, each parameter resulting from movement of the computing device during said capturing step;

creating a signal for each parameter;

determining whether or not each signal is usable for detecting liveness;

determining each signal is usable for detecting liveness; calculating a similarity score, the similarity score indicating the similarity between the signals; and

determining the user is live when the similarity score is at least equal to a threshold score.

2. A method for enhancing user liveness detection in accordance with claim 1 , said calculating parameters step further comprising calculating, for each frame, an angle of light illuminating the biometric data.

3. A method for enhancing user liveness detection in accordance with claim 2 , said calculating parameters step further comprising calculating a second angle for each frame, the second angle being between a plane defined by a front face of the computing device and a vertical axis.

4. A method for enhancing user liveness detection in accordance with claim 1 , said calculating parameters step further comprising:

calculating a perpendicular distance for each point of interest within a field of view of the computing device; and

calculating an angle for each frame, the angle being between a plane defined by a front face of the computing device and a vertical axis.

5. A computing device for enhancing user liveness detection comprising:

a processor; and

a memory configured to store data, said computing device being associated with a network and said memory being in communication with said processor and having instructions stored thereon which, when read and executed by said processor, cause said computing device to:

capture facial images of a user in a video;

calculate parameters for frames included in the video, each parameter resulting from movement of said computing device during capture of the facial images;

create a signal for each parameter;

determine whether each signal is usable for detecting liveness;

when each signal is usable for detecting liveness calculate a similarity score, the similarity score indicating the similarity between the signals; and

determine the user is live when the similarity score is at least equal to a threshold score.

6. A computing device for enhancing user liveness detection in accordance with claim 5 , wherein the instructions when read and executed by said processor, cause said computing device to calculate, for each frame, an angle of light illuminating the biometric data.

7. A computing device for enhancing user liveness detection in accordance with claim 6 , wherein the instructions when read and executed by said processor, cause said computing device to calculate a second angle for each frame, the second angle being between a plane defined by a front face of the computing device and a vertical axis.

8. A computing device for enhancing user liveness detection in accordance with claim 6 , wherein the instructions when read and executed by said processor, cause said computing device to:

calculate a perpendicular distance for each point of interest within a field of view of the computing device; and

calculate an angle for each frame, the angle being between a plane defined by a front face of the computing device and a vertical axis.

9. A method for enhancing user liveness detection comprising:

calculating, by a computing device, an illumination-based parameter for frames included in a video of captured face biometric data, the parameter resulting from movement of the computing device during capture of the biometric data;

creating a signal for the parameter;

calculating a total change in the signal and incremental changes between sequential frames; and

determining the user is live when the signal is monotonous, the total change is at least ten degrees, and the incremental change between all sequential frames is less than twenty percent of the total change.