Obviousness

The provided patent text for US patent 11693938 includes a "Prior art keywords" section listing "user, image, data, authentication, distance," and a "Prior art date" of 2014-08-28. However, it does not contain a "References Cited" section that lists specific prior art patents or publications. Therefore, a direct obviousness analysis by combining specific prior art references, as typically performed under 35 U.S.C. § 103, cannot be conducted with the information at hand.

Instead, this analysis will proceed by considering the general state of the art as implied by the patent's background and the common knowledge of a Person Having Ordinary Skill in the Art (POSITA) around the priority date of August 28, 2014, in the fields of mobile computing, biometric authentication, and facial recognition.

Background State of the Art (as described by the patent):

The patent itself acknowledges several relevant aspects of the prior art:

• Biometric security methods were known, including fingerprint systems, though these were often "prohibitively expensive for use on a small electronic device or are often considered unreliable and unsecure."
• Facial recognition was "generally known and may be used in a variety of contexts."
• "Two-dimensional facial recognition is commonly used to tag people in images on social networks or in photo editing software."
• Crucially, 2D facial recognition was "not considered secure enough" for widespread authentication, because "faces may be photographed or recorded, and then the resulting prints or video displays showing images of the user may be used to trick the system." This highlights a known problem: the vulnerability of 2D facial recognition to spoofing attacks.
• Mobile devices with cameras and movement detecting sensors (e.g., accelerometers, magnetometers, gyroscopes) were commonplace.

Elements of the Independent Claims (1, 10, 18):

The independent claims (1, 10, 18) of US 11693938 generally describe a system and method for facial recognition authentication involving:

1. A mobile computing device with a camera and movement detecting sensors (accelerometer, magnetometer, gyroscope).
2. Capturing a plurality of enrollment images of a user's face while the mobile device is moved.
3. Recording an "enrollment movement" (path parameters) of the mobile device during this imaging using the sensors.
4. Obtaining "enrollment biometrics" from the enrollment images.
5. Storing this enrollment information (biometrics and movement data).
6. For authentication, capturing authentication images while the mobile device is moved.
7. Recording an "authentication movement" (path parameters) of the mobile device during authentication imaging.
8. Obtaining "authentication biometrics" from the authentication images.
9. Comparing the authentication biometrics and authentication movement with the stored enrollment biometrics and enrollment movement to determine whether to authenticate the user.

The core contribution revolves around integrating the device's physical movement during image capture into the biometric authentication process, specifically by recording and comparing "path parameters" from built-in motion sensors.

Obviousness Analysis based on General Knowledge:

Given the patent's description of the prior art, a POSITA in August 2014, seeking to improve the security of facial recognition authentication on mobile devices, would have been motivated to combine existing technologies in a manner that would likely render the claimed invention obvious.

Motivation for Combination:

The primary motivation would be to overcome the well-known vulnerability of 2D facial recognition systems to "spoofing" attacks (e.g., using a photograph or video of an authorized user). A POSITA would recognize that merely matching a static face image is insufficient for secure authentication.

Therefore, the POSITA would seek ways to introduce "liveness detection" or "realness" verification into the authentication process. Integrating dynamic elements that prove the presence of a live, three-dimensional user, interacting with the mobile device, would be a logical step.

Combination of Known Elements:

1. Known Problem: 2D facial recognition was known, but its susceptibility to spoofing by photographs or videos rendered it insecure for high-stakes authentication.
2. Known Technologies:
   • Facial Recognition: Algorithms for detecting and recognizing faces were established.
   • Mobile Devices with Cameras: Smartphones and tablets with front-facing cameras were ubiquitous.
   • Mobile Device Sensors: Accelerometers, gyroscopes, and magnetometers were standard components in mobile devices, providing data on device orientation, movement, speed, and direction.
   • Biometric Liveness Detection: The concept of liveness detection in biometrics (e.g., detecting blinking, head movements, depth perception) was an active area of research to combat spoofing.

Obvious Combination:

A POSITA, faced with the insecurity of 2D facial recognition, would find it obvious to combine:

• 2D Facial Recognition (C): As the primary means of identifying a user visually.
• Mobile Device Camera (A): To capture the user's face.
• Mobile Device Motion Sensors (B): To capture data related to the device's movement.

The motivation for this specific combination arises from the need for enhanced liveness detection. If a fraudster presents a static image or a video, the facial recognition might match, but the device's movement during the authentication process would not correspond to the physical interaction of a live user moving the device to capture varied images.

Therefore, a POSITA would be motivated to:

• Require dynamic interaction: Instead of a static image, instruct the user to move the mobile device relative to their face during image capture.
• Record device movement: Utilize the readily available accelerometer, gyroscope, and magnetometer in the mobile device to record the "path parameters" (e.g., acceleration, angle, speed, distance changes) of this movement during both enrollment and authentication.
• Compare movement data: Compare the recorded authentication movement with a previously enrolled movement pattern. A mismatch in movement data, even if the face itself matches, would strongly indicate a spoofing attempt.

The patent highlights moving the device "in an arc like path horizontally about his or her face" (FIGS. 6A, 6B) or "far away from his or her face, and then brings the mobile device 112 forward closer to his or her face" (FIGS. 7A, 7B). These are straightforward movements that a POSITA would conceive of to generate dynamic image data and corresponding motion sensor data.

The step of comparing "authentication biometrics" with "enrollment biometrics" is a standard facial recognition practice. The crucial addition is the comparison of "authentication movement" with "enrollment movement." This is a direct application of pattern matching techniques (already known in other fields) to the newly collected motion sensor data, motivated by the clear need for anti-spoofing in mobile facial authentication.

In essence, the solution described in the claims – leveraging a mobile device's inherent motion-sensing capabilities to record and verify the dynamic path taken during facial image capture for authentication – addresses a known problem (spoofing in 2D facial recognition) by combining existing technologies (facial recognition, mobile cameras, mobile motion sensors) in a predictable way for a POSITA.