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 .
Claims 1-20 are pending.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12400477 (hereinafter ‘477). Although the claims at issue are not identical, they are not patentably distinct from each other because each of the enumerated instant claims in following table is anticipated by a correspondingly mapped ‘477 claim.
Instant claims
‘477 claims
1. A system for dynamically changing attributes of a card device, comprising:
at least one sensor configured to capture sensor data, wherein the sensor data provides information about an environment around a card device;
a display field configured to display information, comprising a name or a number associated with a first user;
a processor operably coupled to the at least one sensor and the display field, and configured to:
receive a first sensor data from the at least one sensor, wherein the first sensor data indicates presence of the first user around the card device;
extract a set of user features from the first sensor data, wherein the set of user features indicate physical attributes of the first user;
receive a second sensor data from the at least one sensor, wherein the second sensor data indicates presence of a viewer around the card device;
extract a set of viewer features from the second sensor data, wherein the set of viewer features indicate physical attributes of the viewer;
compare at least one of the set of user features with a counterpart feature from among the set of viewer features;
determine that the more than a threshold percentage of the set of user features does not correspond to counterpart features from among the set of viewer features;
determine that the viewer is not the first user in response to determining that more than the threshold percentage of the set of user features does not correspond to the counterpart features from among the set of viewer features; and
in response to determining that the viewer is not the first user, dynamically mask the information displayed on the display field.
2. The system of claim 1, wherein the processor is further configured to, in response to determining that the viewer is not the first user, disable the card device from being used for data communication.
3. The system of claim 1, wherein the processor is further configured to: determine a first pose estimation data associated with the first user based at least in part upon the first sensor data, wherein the first sensor data comprises an image feed of the first user; receive a fourth sensor data from the at least one sensor, wherein the fourth sensor data comprises information about a second user, wherein the information about the second user comprises a second pose estimation associated with the second user; detect a second pose estimation data associated with the second user based at least in part upon the fourth sensor data; compare the first pose estimation data with the second pose estimation data; determine that the first pose estimation data does not correspond to the second pose estimation data; and in response to determining that the first pose estimation data does not correspond to the second pose estimation data, dynamically mask the information displayed on the display field.
4. The system of claim 1, wherein the at least one sensor comprises a camera, a sound sensor, a light sensor, a humidity sensor, a biometric sensor, or a pressure sensor.
5. The system of claim 1, wherein: the set of user features is represented by a user vector comprising a first set of numerical values; the set of viewer features is represented by a viewer vector comprising a second set of numerical values; and comparing the at least one of the extracted user features with the counterpart feature from among the extracted viewer features is in response to comparing at least one of the first set of numerical values with a counterpart numerical value from among the second set of numerical values.
6. The system of claim 5, wherein determining that the first user is not the viewer is in response to determining that more than the threshold percentage of the first set of numerical values does not correspond to the counterpart numerical value from among the second set of numerical values.
7. The system of claim 1, wherein the processor is further configured to: detect that a message is received at the card device; and dynamically mask the message in response to determining that the determined distance is less than the threshold distance and that the viewer is not the first user.
8. A method for dynamically changing attributes of a card device, comprising:
receiving a first sensor data from at least one sensor associated with a card device, wherein the first sensor data indicates presence of a first user around the card device;
extracting a set of user features from the first sensor data, wherein the set of user features indicate physical attributes of the first user;
receiving a second sensor data from the at least one sensor, wherein the second sensor data indicates presence of a viewer around the card device;
extracting a set of viewer features from the second sensor data, wherein the set of viewer features indicate physical attributes of the viewer;
comparing at least one of the set of user features with a counterpart feature from among the set of viewer features;
determining that more than a threshold percentage of the set of user features does not correspond to counterpart features from among the set of viewer features;
determining that the viewer is not the first user in response to determining that more than the threshold percentage of the set of user features does not correspond to the counterpart features from among the set of viewer features; and
in response to determining that the viewer is not the first user, dynamically masking the information displayed on a display field.
9. The method of claim 8, further comprising, in response to determining that the viewer is not the first user, disabling the card device from being used for data communication.
10. The method of claim 8, further comprising: determining a first pose estimation data associated with the first user based at least in part upon the first sensor data, wherein the first sensor data comprises an image feed of the first user; receiving a fourth sensor data from the at least one sensor, wherein the fourth sensor data comprises information about a second user, wherein the information about the second user comprises a second pose estimation associated with the second user; detecting a second pose estimation data associated with the second user based at least in part upon the fourth sensor data; comparing the first pose estimation data with the second pose estimation data; determining that the first pose estimation data does not correspond to the second pose estimation data; and in response to determining that the first pose estimation data does not correspond to the second pose estimation data, dynamically masking the information displayed on the display field.
11. The method of claim 8, wherein the at least one sensor comprises a camera, a sound sensor, a light sensor, a humidity sensor, a biometric sensor, or a pressure sensor.
12. The method of claim 8, wherein: the set of user features is represented by a user vector comprising a first set of numerical values; the set of viewer features is represented by a viewer vector comprising a second set of numerical values; and comparing the at least one of the extracted user features with the counterpart feature from among the extracted viewer features is in response to comparing at least one of the first set of numerical values with a counterpart numerical value from among the second set of numerical values.
13. The method of claim 12, wherein determining that the first user is not the viewer is in response to determining that more than the threshold percentage of the first set of numerical values does not correspond to the counterpart numerical value from among the second set of numerical values.
8. method of claim 8, further comprising: detecting that a message is received at the card device; and dynamically masking the message in response to determining that the determined distance is less than the threshold distance and that the viewer is not the first user.
15. A non-transitory computer-readable medium storing instructions that when executed by a processor, cause the processor to:
receive a first sensor data from at least one sensor associated with a card device, wherein the first sensor data indicates presence of the first user around the card device;
extract a set of user features from the first sensor data, wherein the set of user features indicate physical attributes of the first user;
receive a second sensor data from the at least one sensor, wherein the second sensor data indicates presence of a viewer around the card device;
extract a set of viewer features from the second sensor data, wherein the set of viewer features indicate physical attributes of the viewer;
compare at least one of the set of user features with a counterpart feature from among the set of viewer features;
determine that the more than a threshold percentage of the set of user features does not correspond to counterpart features from among the set of viewer features;
determine that the viewer is not the first user in response to determining that more than the threshold percentage of the set of user features does not correspond to the counterpart features from among the set of viewer features; and
in response to determining that the viewer is not the first user, dynamically mask the information displayed on a display field.
16. The non-transitory computer-readable medium of claim 15, wherein the instructions further cause the processor to, in response to determining that the viewer is not the first user, disable the card device from being used for data communication.
17. The non-transitory computer-readable medium of claim 15, wherein the instructions further cause the processor to: determine a first pose estimation data associated with the first user based at least in part upon the first sensor data, wherein the first sensor data comprises an image feed of the first user; receive a fourth sensor data from the at least one sensor, wherein the fourth sensor data comprises information about a second user, wherein the information about the second user comprises a second pose estimation associated with the second user; detect a second pose estimation data associated with the second user based at least in part upon the fourth sensor data; compare the first pose estimation data with the second pose estimation data; determine that the first pose estimation data does not correspond to the second pose estimation data; and in response to determining that the first pose estimation data does not correspond to the second pose estimation data, dynamically mask the information displayed on the display field.
18. The non-transitory computer-readable medium of claim 17, wherein: the first pose estimation data is represented by a first pose estimation vector comprising a third set of numerical values; the second pose estimation data is represented by a second pose estimation vector comprising a fourth set of numerical values; determining that the first pose estimation data does not correspond to the second pose estimation data is in response to: comparing the first pose estimation vector with the second pose estimation vector; and determining that more than a threshold numerical values of the third set of numerical values does not correspond to counterpart numerical values from among the fourth set of numerical values.
19. The non-transitory computer-readable medium of claim 15, wherein the distance between the viewer and the card device is determined from an image of the viewer captured by a camera sensor from among the at least one sensor.
20. The non-transitory computer-readable medium of claim 15, wherein: the set of user features is represented by a user vector comprising a first set of numerical values; the set of viewer features is represented by a viewer vector comprising a second set of numerical values; and comparing the at least one of the extracted user features with the counterpart feature from among the extracted viewer features is in response to comparing at least one of the first set of numerical values with a counterpart numerical value from among the second set of numerical values.
1. A system for dynamically changing attributes of a card device, comprising:
at least one sensor configured to capture sensor data, wherein the sensor data provides information about an environment around a card device,
wherein the information about the environment indicates objects located within the environment around the card device;
a display field configured to display information, comprising a name or a number associated with a first user;
a processor operably coupled to the at least one sensor and the display field, and configured to:
receive a first sensor data from the at least one sensor, wherein the first sensor data indicates presence of the first user around the card device;
extract a set of user features from the first sensor data, wherein the set of user features indicate physical attributes of the first user;
receive a second sensor data from the at least one sensor, wherein the second sensor data indicates presence of a viewer around the card device;
extract a set of viewer features from the second sensor data, wherein the set of viewer features indicate physical attributes of the viewer;
compare at least one of the set of user features with a counterpart feature from among the set of viewer features;
determine that the more than a threshold percentage of the set of user features does not correspond to counterpart features from among the set of viewer features;
determine that the viewer is not the first user in response to determining that more than the threshold percentage of the set of user features does not correspond to the counterpart features from among the set of viewer features;
determine a distance between the viewer and the card device;
compare the determined distance with a threshold distance;
determine that the determined distance is less than the threshold distance; and
in response to determining that the determined distance is less than the threshold distance and that the viewer is not the first user, dynamically mask the information displayed on the display field.
2. The system of claim 1, wherein the processor is further configured to, in response to determining that the determined distance is less than the threshold distance and that the viewer is not the first user, disable the card device from being used for data communication.
3. The system of claim 1, wherein the processor is further configured to: determine a first pose estimation data associated with the first user based at least in part upon the first sensor data, wherein the first sensor data comprises an image feed of the first user; receive a fourth sensor data from the at least one sensor, wherein the fourth sensor data comprises information about a second user, wherein the information about the second user comprises a second pose estimation associated with the second user; detect a second pose estimation data associated with the second user based at least in part upon the fourth sensor data; compare the first pose estimation data with the second pose estimation data; determine that the first pose estimation data does not correspond to the second pose estimation data; and in response to determining that the first pose estimation data does not correspond to the second pose estimation data, dynamically mask the information displayed on the display field.
4. The system of claim 1, wherein the at least one sensor comprises a camera, a sound sensor, a light sensor, a humidity sensor, a biometric sensor, or a pressure sensor.
5. The system of claim 1, wherein: the set of user features is represented by a user vector comprising a first set of numerical values; the set of viewer features is represented by a viewer vector comprising a second set of numerical values; and comparing the at least one of the extracted user features with the counterpart feature from among the extracted viewer features is in response to comparing at least one of the first set of numerical values with a counterpart numerical value from among the second set of numerical values.
6. The system of claim 5, wherein determining that the first user is not the viewer is in response to determining that more than the threshold percentage of the first set of numerical values does not correspond to the counterpart numerical value from among the second set of numerical values.
7. The system of claim 1, wherein the processor is further configured to: detect that a message is received at the card device; and dynamically mask the message in response to determining that the determined distance is less than the threshold distance and that the viewer is not the first user.
8. A method for dynamically changing attributes of a card device, comprising:
receiving a first sensor data from at least one sensor associated with a card device, wherein the first sensor data indicates presence of the first user around the card device;
extracting a set of user features from the first sensor data, wherein the set of user features indicate physical attributes of the first user;
receiving a second sensor data from the at least one sensor, wherein the second sensor data indicates presence of a viewer around the card device;
extracting a set of viewer features from the second sensor data, wherein the set of viewer features indicate physical attributes of the viewer;
comparing at least one of the set of user features with a counterpart feature from among the set of viewer features;
determining that the more than a threshold percentage of the set of user features does not correspond to counterpart features from among the set of viewer features;
determining that the viewer is not the first user in response to determining that more than the threshold percentage of the set of user features does not correspond to the counterpart features from among the set of viewer features;
determining a distance between the viewer and the card device;
comparing the determined distance with a threshold distance;
determining that the determined distance is less than the threshold distance; and
in response to determining that the determined distance is less than the threshold distance and that the viewer is not the first user, dynamically masking the information displayed on a display field.
9. The method of claim 8, further comprising, in response to determining that the determined distance is less than the threshold distance and that the viewer is not the first user, disabling the card device from being used for data communication.
10. The method of claim 8, further comprising: determining a first pose estimation data associated with the first user based at least in part upon the first sensor data, wherein the first sensor data comprises an image feed of the first user; receiving a fourth sensor data from the at least one sensor, wherein the fourth sensor data comprises information about a second user, wherein the information about the second user comprises a second pose estimation associated with the second user; detecting a second pose estimation data associated with the second user based at least in part upon the fourth sensor data; comparing the first pose estimation data with the second pose estimation data; determining that the first pose estimation data does not correspond to the second pose estimation data; and in response to determining that the first pose estimation data does not correspond to the second pose estimation data, dynamically masking the information displayed on the display field.
11. The method of claim 8, wherein the at least one sensor comprises a camera, a sound sensor, a light sensor, a humidity sensor, a biometric sensor, or a pressure sensor.
12. The method of claim 8, wherein: the set of user features is represented by a user vector comprising a first set of numerical values; the set of viewer features is represented by a viewer vector comprising a second set of numerical values; and comparing the at least one of the extracted user features with the counterpart feature from among the extracted viewer features is in response to comparing at least one of the first set of numerical values with a counterpart numerical value from among the second set of numerical values.
13. The method of claim 12, wherein determining that the first user is not the viewer is in response to determining that more than the threshold percentage of the first set of numerical values does not correspond to the counterpart numerical value from among the second set of numerical values.
14. The method of claim 8, further comprising: detecting that a message is received at the card device; and dynamically masking the message in response to determining that the determined distance is less than the threshold distance and that the viewer is not the first user.
15. A non-transitory computer-readable medium storing instructions that when executed by a processor, cause the processor to:
receive a first sensor data from at least one sensor associated with a card device, wherein the first sensor data indicates presence of the first user around the card device;
extract a set of user features from the first sensor data, wherein the set of user features indicate physical attributes of the first user;
receive a second sensor data from the at least one sensor, wherein the second sensor data indicates presence of a viewer around the card device;
extract a set of viewer features from the second sensor data, wherein the set of viewer features indicate physical attributes of the viewer;
compare at least one of the set of user features with a counterpart feature from among the set of viewer features;
determine that the more than a threshold percentage of the set of user features does not correspond to counterpart features from among the set of viewer features;
determine that the viewer is not the first user in response to determining that more than the threshold percentage of the set of user features does not correspond to the counterpart features from among the set of viewer features; determine a distance between the viewer and the card device; compare the determined distance with a threshold distance; determine that the determined distance is less than the threshold distance; and
in response to determining that the determined distance is less than the threshold distance and that the viewer is not the first user, dynamically mask the information displayed on a display field.
16. The non-transitory computer-readable medium of claim 15, wherein the instructions further cause the processor to, in response to determining that the determined distance is less than the threshold distance and that the viewer is not the first user, disable the card device from being used for data communication.
17. The non-transitory computer-readable medium of claim 15, wherein the instructions further cause the processor to: determine a first pose estimation data associated with the first user based at least in part upon the first sensor data, wherein the first sensor data comprises an image feed of the first user; receive a fourth sensor data from the at least one sensor, wherein the fourth sensor data comprises information about a second user, wherein the information about the second user comprises a second pose estimation associated with the second user; detect a second pose estimation data associated with the second user based at least in part upon the fourth sensor data; compare the first pose estimation data with the second pose estimation data; determine that the first pose estimation data does not correspond to the second pose estimation data; and in response to determining that the first pose estimation data does not correspond to the second pose estimation data, dynamically mask the information displayed on the display field.
18. The non-transitory computer-readable medium of claim 17, wherein: the first pose estimation data is represented by a first pose estimation vector comprising a third set of numerical values; the second pose estimation data is represented by a second pose estimation vector comprising a fourth set of numerical values; determining that the first pose estimation data does not correspond to the second pose estimation data is in response to: comparing the first pose estimation vector with the second pose estimation vector; and determining that more than a threshold numerical values of the third set of numerical values does not correspond to counterpart numerical values from among the fourth set of numerical values.
19. The non-transitory computer-readable medium of claim 15, wherein the distance between the viewer and the card device is determined from an image of the viewer captured by a camera sensor from among the at least one sensor.
20. The non-transitory computer-readable medium of claim 15, wherein: the set of user features is represented by a user vector comprising a first set of numerical values; the set of viewer features is represented by a viewer vector comprising a second set of numerical values; and comparing the at least one of the extracted user features with the counterpart feature from among the extracted viewer features is in response to comparing at least one of the first set of numerical values with a counterpart numerical value from among the second set of numerical values.
Claim Rejections - 35 USC § 103
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, 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, 3, 4, 8, 10, 11, 15, 17 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Singh US 20210374275, in view of Pantazelos US 20220366063.
For claims 1, 8 and 15, Singh discloses:
A system for dynamically changing attributes of a card device, comprising:
at least one sensor configured to capture sensor data, wherein the sensor data provides information about an environment around a card device (par. 0016: Image capturing engine…receive images of the viewers 110 within a visual field of interest 120 from camera 106 of user device 102.);
a display field configured to display information, comprising a name or a number associated with a first user (par. 0035: “…examples of sensitive information may include personal information of employees, bank account numbers”; par. 0004: “…the system is able to protect sensitive and confidential information from being exposed and displayed on a display screen of any computing device (e.g., a phone, a laptop…) to any viewer who is not authorized to view the sensitive information”);
a processor operably coupled to the at least one sensor and the display field (par. 0032), and configured to:
receive a first sensor data from the at least one sensor, wherein the first sensor data indicates presence of the first user around the card device (par. 0016: “The image capturing engine 124 is also configured to capture the images of the viewers 110…the image capturing engine 124 may then transmit the received images to a deep learning system engine 154 in server 140 via network 170.”);
extract a set of user features from the first sensor data, wherein the set of user features indicate physical attributes of the first user (par. 0025: “The deep learning system engine 154 is configured to identify the viewers 110 using any suitable facial recognition algorithm.”; par. 0017: “The image capturing engine 124 is also configured to determine distance 114 of each of the viewers 110 from user device 102”);
receive a second sensor data from the at least one sensor, wherein the second sensor data indicates presence of a viewer around the card device (par. 0016: “The image capturing engine 124 is also configured to capture the images of the viewers 110…the image capturing engine 124 may then transmit the received images to a deep learning system engine 154 in server 140 via network 170.”);
extract a set of viewer features from the second sensor data, wherein the set of viewer features indicate physical attributes of the viewer (par. 0025: “The deep learning system engine 154 is configured to identify the viewers 110 using any suitable facial recognition algorithm.”; par. 0017: “The image capturing engine 124 is also configured to determine distance 114 of each of the viewers 110 from user device 102”);
compare at least one of the set of user features with a counterpart feature from among the set of viewer features (par. 0025: “…the deep learning system engine 154 identifies the viewers 110 by searching for each viewer's 110 image in viewer's profile database 162 in memory 160, and for each of the viewers 110, matching viewer's 110 image to one of the stored viewer's profiles 164.”);
in response to determining that the viewer is not the first user, dynamically mask the information displayed on the display field (par. 0027: “…the masking rule engine 156 is configured to dynamically mask an item 108 containing sensitive information if at least one viewer among viewers 110 is at distance 114 that is within a dynamic proximity threshold 112 of item 108 containing sensitive information and that viewer is not authorized to view the item 108.”).
Singh fails to explicitly disclose:
“determine that the more than a threshold percentage of the set of user features does not correspond to counterpart features from among the set of viewer features;
determine that the viewer is not the first user in response to determining that more than the threshold percentage of the set of user features does not correspond to the counterpart features from among the set of viewer features”.
However, in a related field, Pantazelos discloses “…the server(s) 130 and/or the creator computing device 102 determine whether the facial recognition match percentage, determined in step 211, is greater than or equal to a threshold facial recognition match percentage….If the creator 112 passes facial authentication (i.e., step 212=yes), the method 20 proceeds…” (par. 0040).
It would have been obvious to one of ordinary skill before effective filing date of instant claimed invention to have introduced Pantazelos’ teaching alongside Singh. The motivation to combine would have been to utilize well-known technique of threshold-based assessment of biometric matching in order to achieve predictable result of authenticating user access on basis of sufficiently high confidence of their identity.
For claims 3, 10 and 17, Singh-Pantazelos discloses:
The system of claim 1, wherein the processor is further configured to: determine a first pose estimation data associated with the first user based at least in part upon the first sensor data, wherein the first sensor data comprises an image feed of the first user (Singh, par. 0016: “The image capturing engine 124 may use any appropriate image classification algorithm to detect whether any of the viewers 110 are facing the user device 102 (e.g., user device 102a, 102b, and 102c). For example, an image classification neural network may be trained by a training dataset that includes viewers' 110 images facing the camera 106 taking the images and facing other directions, where each image is labeled whether the viewer 110 is facing the camera 106 or not based on the location of the eyes of the viewer 110 in each image.”); receive a fourth sensor data from the at least one sensor, wherein the fourth sensor data comprises information about a second user, wherein the information about the second user comprises a second pose estimation associated with the second user; detect a second pose estimation data associated with the second user based at least in part upon the fourth sensor data (Singh, par. 0016: “The image capturing engine 124 may use any appropriate image classification algorithm to detect whether any of the viewers 110 are facing the user device 102 (e.g., user device 102a, 102b, and 102c). For example, an image classification neural network may be trained by a training dataset that includes viewers' 110 images facing the camera 106 taking the images and facing other directions, where each image is labeled whether the viewer 110 is facing the camera 106 or not based on the location of the eyes of the viewer 110 in each image.”); compare the first pose estimation data with the second pose estimation data; determine that the first pose estimation data does not correspond to the second pose estimation data (par. 0025: Deep learning system engine performs facial recognition of captured persons); and in response to determining that the first pose estimation data does not correspond to the second pose estimation data, dynamically mask the information displayed on the display field (Singh, par. 0027: “Masking rule engine 156 is configured to receive the dynamic proximity thresholds of items 108 containing sensitive information from the dynamic proximity threshold engine 152, information regarding whether each of the viewers 110 in the visual field of interest 120 is authorized to view each of the items 108 containing sensitive information from the deep learning system engine 154, and the distance 114 of each of the viewers 110 from the image capturing engine 124 via network 170. Then, based on this received information, the masking rule engine 156 is configured to dynamically mask an item 108 containing sensitive information…”).
For claims 4 and 11, Singh-Pantazelos discloses:
The system of claim 1, wherein the at least one sensor comprises a camera, a sound sensor, a light sensor, a humidity sensor, a biometric sensor, or a pressure sensor (Singh, par. 0016: camera 106 disclosed).
For claim 19, Singh-Pantazelos discloses:
The non-transitory computer-readable medium of Claim 15, wherein the distance between the viewer and the card device is determined from an image of the viewer captured by a camera sensor from among the at least one sensor (Singh, par. 0017: “The image capturing engine 124 is also configured to determine distance 114 of each of the viewers 110 from user device 102”).
Claims 2, 9 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Singh US 20210374275, in view of Pantazelos US 20220366063, in view of Halstuch US 20230032139.
For claims 2, 9 and 16, Singh-Pantazelos discloses:
The system of Claim 1, but fails to teach “wherein the processor is further configured to, in response to determining that the viewer is not the first user, disable the card device from being used for data communication.”
However, in a related field, Halstuch teaches user/device network access being restricted until the user re-authenticates (par. 0021 and 0022). Multi-factor authentication utilized to authenticate user of tablet computer, PDA, mobile telephone, and the like (par. 0025, 0026).
It would have been obvious to one of ordinary skill before effective filing date of instant claimed invention to have introduced Halstuch’s teaching alongside the combination. The motivation to combine would have been to ensure network security by enforcing security policies set by an organization (Halstuch, par. 0021 and 0022).
Claims 5, 6, 12, 13, 18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Singh US 20210374275, in view of Pantazelos US 20220366063, in view of Xiong US 20220374635.
For claims 5, 12 and 20 Singh-Pantazelos discloses:
The system of claim 1, but fails to explicitly disclose ”wherein: the set of user features is represented by a user vector comprising a first set of numerical values; the set of viewer features is represented by a viewer vector comprising a second set of numerical values; and comparing the at least one of the extracted user features with the counterpart feature from among the extracted viewer features is in response to comparing at least one of the first set of numerical values with a counterpart numerical value from among the second set of numerical values.”
However, in a related field, Xiong discloses “a facial recognition model may apply a set of weighted parameter values representing the relationships among sets of feature vectors for comparison with reference data (such as sets of feature vectors for known faces) and determination of a probabilistic reliability or correlation factor. Analytical model library 346 may include or access object reference data 344.2 for matching detected objects with previously identified (or recognized) reference objects…. For example, the facial recognition model may return one or more known individuals from the reference data and corresponding reliability values, assuming at least one match is found that meets a threshold reliability value.” (par. 0091).
It would have been obvious to one of ordinary skill before effective filing date of instant claimed invention to have introduced Xiong’s teaching alongside the combination. The motivation to combine would have been to utilize well-known technique of threshold-based assessment of biometric feature matching in order to achieve predictable result of authenticating user on basis of sufficiently high confidence of their identity.
For claims 6 and 13, Singh-Pantazelos-Xiong discloses:
The system of claim 5, wherein determining that the first user is not the viewer is in response to determining that more than the threshold percentage of the first set of numerical values does not correspond to the counterpart numerical value from among the second set of numerical values (Xiong, par. 0091).
For claim 18, Singh-Pantazelos-Xiong discloses:
The non-transitory computer-readable medium of claim 17 wherein the first pose estimation data (Singh, par. 0016: “The image capturing engine 124 may use any appropriate image classification algorithm to detect whether any of the viewers 110 are facing the user device 102 (e.g., user device 102a, 102b, and 102c). For example, an image classification neural network may be trained by a training dataset that includes viewers' 110 images facing the camera 106 taking the images and facing other directions, where each image is labeled whether the viewer 110 is facing the camera 106 or not based on the location of the eyes of the viewer 110 in each image.”) is represented by a first pose estimation vector comprising a third set of numerical values; the second pose estimation data is represented by a second pose estimation vector comprising a fourth set of numerical values; determining that the first pose estimation data does not correspond to the second pose estimation data is in response to: comparing the first pose estimation vector with the second pose estimation vector; and determining that more than a threshold numerical values of the third set of numerical values does not correspond to counterpart numerical values from among the fourth set of numerical values “a facial recognition model may apply a set of weighted parameter values representing the relationships among sets of feature vectors for comparison with reference data (such as sets of feature vectors for known faces) and determination of a probabilistic reliability or correlation factor. Analytical model library 346 may include or access object reference data 344.2 for matching detected objects with previously identified (or recognized) reference objects…. For example, the facial recognition model may return one or more known individuals from the reference data and corresponding reliability values, assuming at least one match is found that meets a threshold reliability value.” (par. 0091).
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Singh US 20210374275, in view of Pantazelos US 20220366063, in view of Shah USP 12118050.
For claims 7 and 14, Singh-Pantazelos discloses:
The system of claim 1, wherein the processor is further configured to: dynamically mask the message in response to determining that the determined distance is less than the threshold distance and that the viewer is not the first user (Singh, par. 0027: “…the masking rule engine 156 is configured to dynamically mask an item 108 containing sensitive information if at least one viewer among viewers 110 is at distance 114 that is within a dynamic proximity threshold 112 of item 108 containing sensitive information and that viewer is not authorized to view the item 108.”).
The combination fails to explicitly disclose “detect that a message is received at the card device”. However, in a related filed, Shah discloses a client “device dynamically generate[s] and display contextually-relevant information cards in response to certain actions being performed on the client device 110 or certain conditions of the client device 110 being detected”. “[T]he application may allow the client device 110 to obtain and provide information from the source database 130…through information cards that can be dynamically adjusted based on….device notifications, messages (e.g., e-mails or SMS text messages)…” (col 5, ll 20-39). Furthermore, Shah teaches obscuring sensitive data responsive to additional, unauthorized users being present in room/area (col. 7, ll35-56).
It would have been obvious to one of ordinary skill before effective filing date of instant claimed invention to have introduced Shah’s teaching alongside the combination. The motivation to combine would have been to prevent confidential/private information from being accessible to unauthorized persons (Shah, col 7, ll46-56).
Conclusion
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/CLAYTON R WILLIAMS/Primary Examiner, Art Unit 2443
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