DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-11 are rejected under 35 U.S.C 103 as being unpatentable over Barry et al. (US 2016/0308859), hereon referred to as Barry, in view of Figueredo de Santana et al. (US 2020/0272717), and hereon referred to as Santana.
In regards to claims 1 & 9, Barry discloses capturing, by an image capturing unit [102], at least one image of the user (A camera system, of one or more cameras, capable capturing video and still images of the user in two dimensions, three dimensions or both; Paragraphs 0064; 0082); analyzing, by an analyzer module [104], the at least one captured image(s) of the user to detect a face corresponding to the pre-defined parameters being conformed ( Face finding: The device automatically determines the location of the user's head and face in preparation for finding detail features on the face; Paragraphs 0143-0147; 0172); cropping out, by a cropping module [106], the detected face from the at least one captured image to form a cropped face image (Face cropping: The device may automatically bound the face area to define the region to receive subsequent detail processing; Paragraphs 0143-0147); extracting, by an extraction module [108], one or more features from the cropped face image (Feature Localization: The device automatically identifies and locates specific features on the face to support biometric measurements, face image registration and face image scaling. This process may support subsequent measurement, analysis and compensation of pose variations and off axis lighting components to help ensure repeatable and accurate recognition results. Feature localization may use two dimensional data, three dimensional data; Paragraphs 0143-0146); and authenticating, by an authentication module [114], the user based on a positive matching of the extracted one or more features of the cropped face image with the set of data corresponding to the user (if a match is sufficiently close to a person stored in the database, then the user is authenticated. If the authenticated user is also authorized to pass through the portal, then the user may be granted access; Paragraphs 0120-0130).
However, Barry does not disclose comparing, by a comparing module [110], the extracted one or more features of the cropped face image with a set of data associated with a plurality of users, wherein the set of data associated with the plurality of users is stored in one or more database repositories. In an analogous art Santana discloses comparing, by a comparing module [110], the extracted one or more features of the cropped face image with a set of data associated with a plurality of users, wherein the set of data associated with the plurality of users is stored in one or more database repositories [120] (each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s); The networked computer environment 100 may include a computer 102 with a processor 104 and a data storage device; Paragraphs 0020-0030).
At the time before the effective filing date of the invention, it would have been obvious to the one with ordinary skill in the art to combine the teachings disclosed by Barry, with the teachings disclosed by Santana comparing, by a comparing module [110], the extracted one or more features of the cropped face image with a set of data associated with a plurality of users, wherein the set of data associated with the plurality of users is stored in one or more database repositories. The suggestion/motivation of the combination would have been to provide additional security by providing access control using multi-authentication factors (Santana; Abs).
In regards to claim 2, Barry discloses wherein the pre-defined parameters at the step of analyzing the at least one captured image(s) of the user includes verifying realness (liveness) or fakeness (non-live, fabricated or synthetic) of the at least one captured image(s) of the user (The device is capable of directly testing for spoofing using devices that may perform:. Detecting the user's heart rate through video data. A flash or momentary light of a prescribed intensity and spectral composition may be directed at the user requesting access to induce a retro-reflection from the front or back of one or both of the user's eye ball or retina. The unique reflection resulting from each eye, and two eyes together, is known for being extremely difficult to reproduce in the absence of a real person requesting access; Paragraphs 0164-0169).
In regards to claims 3 & 10, Barry discloses wherein authenticating the user via face recognition is performed inter-operably by utilizing the one or more database repositories [120] located at the one or more devices or servers ( Each newly created characteristic vector 87 can be compared with preexisting characteristic vectors 88 stored in a database 89. FIG. 5 shows the stored vectors within the device but these could alternatively reside outside of the device, such as in a PACS controller or in the cloud; Paragraphs 0155-0160).
In regards to claim 4, Barry discloses wherein the set of data contains previously stored facial features of registered users (This characterization is then compared by the device to the device's stored list of authorized users who have been previously characterized, or enrolled, in a consistent manner. If a sufficiently strong match is found then the biometric authentication is deemed satisfied and the user is subsequently authorized access in accordance with the portal's prevailing security protocol; Paragraphs 0100-0105).
In regards to claim 5, Santana discloses wherein the authentication of the user via face recognition is performed in an online mode and offline mode, such that the offline mode for the authentication of the user includes a local computation & Artificial Intelligence (AI) processing of the face recognition without any dependency of internet and then data synchronization between the one or more devices and server once internet connectivity is restored (the access control program 110a, 110b may utilize deep neural networks, such as a CNN, to recognize the detected faces as representations of the authorized user. In one embodiment, the access control program 110a, 110b may feed the training data into the CNN which may then output a quantified representation of each detected face in the training data. The quantified representation of each detected face may be returned from the CNN as a feature vector (e.g., multi-dimensional data) corresponding to embedded facial measurements (e.g., geometry of the facial elements, relative spatial location of the facial elements, three-dimensional geometry of the face, and other facial features) that may be unique to a specific face, such as the face of the user; Paragraphs 0043; 0050-0055).
In regards to claim 6, Barry discloses wherein face images of the one or more users along with pre-defined associated parameters of the user(s) are pre-stored in the one or more database repositories [120] prior to the authentication of the user via face recognition (The administrator will also collect a face image or images of the user that may contain two or three dimensional data, and may collect voice data. This biometric data may be collected with the access control device of the present inventive concepts or some other image and voice capture device. The biometric image and voice data collected for enrollment is then reduced to a characteristic vector in the same manner as done by the access control devices located at secured portals as described by the present inventive concepts; Paragraphs 0171-0172).
In regards to claims 7 & 11, Barry discloses wherein the set of data associated with the plurality of users is stored by:- capturing, by the image capturing unit [102], at least one image of each of the plurality of users;- analyzing, by the analyzer module [104], the at least one captured image(s) of each of the plurality of users to detect face(s) corresponding to the pre- defined parameters being conformed; - cropping out, by the cropping module [106], the detected face(s) from the at least one captured image to form the cropped face images; - extracting, by an extraction module [108], one or more features from the cropped face images of each of the plurality of users; and - storing, at the one or more database repositories [120], the extracted one or more features from the cropped face images of the plurality of users to form the set of data associated with the plurality of users (The administrator will also collect a face image or images of the user that may contain two or three dimensional data, and may collect voice data. This biometric data may be collected with the access control device of the present inventive concepts or some other image and voice capture device. The biometric image and voice data collected for enrollment is then reduced to a characteristic vector in the same manner as done by the access control devices located at secured portals as described by the present inventive concepts. User enrollment data including at least one of the characteristic vectors, a knowledge solution (such as secure PINs, passwords or phrases) and a possession solution (such as a secure mobile device authentication data) is forwarded to each device of the present inventive concepts that the user will be authorized to use. In this manner, the device is primed and ready to authenticate the user through all applicable multi-factor authentication tests; Paragraphs 0170-0172).
In regards to claim 8, Santana discloses wherein the one or more database repositories [120] are located at one or more devices including, but not limited to, server, edge devices, mobile devices, laptops, and/or computers (the access control program 110a, 110b may interact with a database 114 that may be embedded in various storage devices, such as, but not limited to a computer/mobile device 102, a networked server 112, or a cloud storage service; Paragraphs 0030-0035).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHARIF E ULLAH whose telephone number is (571)272-5453. The examiner can normally be reached Mon-Fri 7:00-5:30.
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/SHARIF E ULLAH/Primary Examiner, Art Unit 2495
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