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 .
Response to Amendment
In response to applicant’s amendment received on 9/2/2025, all requested changes to the specification and claims have been entered. Claims 1-30 were previously and are currently pending. The amendments have resolved the pending claim objections, 112(a) rejections, and112(b) rejections, all of which are herein withdrawn. Additionally, the amendments have resolved the previously indicated issues with priority, those issues are herein withdrawn, and all the claims in the current amendment are now entitled to the priority date of 8/9/2019.
Terminal Disclaimer
The terminal disclaimer filed on 9/2/2025 disclaiming the terminal portion of any patent granted on this application which would extend beyond the expiration date of USPN 11,250,266 and USPN 12,050,673 has been reviewed and is accepted. The terminal disclaimer has been recorded and the pending double patenting rejections are herein withdrawn.
Response to Arguments
Applicant’s arguments with respect to the prior art rejections of claim(s) 1, 16 and 22 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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 1-6, 8-10, 16-19, 22-26, 29 and 30 are rejected under 35 U.S.C. 103 as being unpatentable over US 2016/0132720 to Klare et al. (“Klare”) in view of US2018/0293429 to Wechsler et al. (“Wechsler”), in further view of US 2014/0237610 to Vandervort.
Regarding claim 1, Klare discloses a method comprising:
obtaining, by a server from one or more publicly accessible sites, reference facial recognition data, wherein the reference facial recognition data comprises a plurality of vector representations, each associated with a face or a plurality of faces (Fig. 1, elements 102 and 108; Fig. 2; paragraphs 41-43 and 45-47, where the combination of search (108) and ingestion (102) systems corresponds to the broadest reasonable interpretation of a “server” in which a remote system or process is serving a client/user device through a network, where facial images are obtained via public or private sources (e.g. public URL) and a face recognition algorithm (104) generates reference facial recognition data from the face in the image in the form of feature vector representations for each);
storing the reference facial recognition data and image source information associated with the facial recognition data in a database (Fig. 1, element 106; paragraph 42, wherein the reference facial recognition data (i.e. feature vector) and image source information (e.g. URL) are stored together in the gallery files database);
receiving an image from a user device, wherein the image comprises at least one face of a subject (Fig. 1, element 110; Fig. 4; paragraphs 43-44, 48 and 54, wherein a query face image is provided by a user device and received by the search system);
generating facial recognition data comprising a vector representation of the at least one face (Fig. 1, elements 110, 108, 104; Fig. 3; Fig. 5A-5C; paragraphs 48, 49, 67, wherein the query face image is transformed into a feature vector corresponding to the facial recognition data);
comparing, by the server Fig. 3; paragraphs 50, 51, 69 and 70, wherein the query facial recognition data/vectors are compared to reference facial recognition data/vectors by the search system of the “server”);
identifying, based on a comparison of the facial recognition data to the reference facial recognition data, one or more candidates that match the at least one face (Fig. 3; Fig. 4; paragraphs 50, 51, 54, 69 and 70, wherein based on comparison of the vectors, candidates with similar/matching faces are identified);
based on identification of the one or more candidates matching the at least one face, retrieving, from the database, more candidates (Fig. 1; Fig. 3; Fig. 4; paragraphs 42, 51-54, wherein when a match is determined candidate metadata such as source information (i.e. URL that identifies a source of the image corresponds to the link to an online profile associated with the candidate) is retrieved from the database/gallery); and
sending, to the user device, an image of the one or more candidates and the image source information (Fig. 1; Fig. 3; Fig. 4; paragraphs 42, 51-54, wherein the matched images and metadata such as source information (i.e. URL that identifies a source of the image) are transmitted back to the user’s device for display).
Klare does not disclose expressly that comparing facial recognition data (i.e. vectors) is performed using a machine learning module, or retrieving, from a database, based on a predetermined privacy setting of the identified candidate, image source information.
Wechsler discloses a process of comparing facial recognition data using a machine learning module to generate the facial recognition data in the form of feature vectors that are used for the comparison (Fig. 4; paragraphs 22-24).
Klare & Wechsler are combinable because they are from the same art of image processing, specifically facial image processing.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of comparing facial recognition data using a machine learning module to generate the facial recognition data in the form of feature vectors that are used for the comparison, as taught by Wechsler, into the process comparing query and reference facial recognition data disclosed by Klare.
The suggestion/motivation for doing so would have been to provide better recognition performance (Wechsler, paragraph 07).
Additionally, Vandervort discloses a process for retrieving, from a database, based on a predetermined privacy setting of an identified candidate, information associated with the candidate (Figs. 4, 5; paragraphs 10, 11, 48-50, wherein a candidate configures the privacy settings that regulate the information associated with them that can be retrieved).
Klare & Vandervort are combinable because they are from the same art of data retrieval associated with an individual.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of retrieving, from a database, based on a predetermined privacy setting of an identified candidate, information associated with the candidate, as taught by Vandervort, into the process of, based on identification of the one or more candidates matching the at least one face, retrieving, from the database, image source information associated with each of the one or more candidates, wherein the image source information comprises a link to an online webpage associated with the one or more candidates disclosed by Klare.
The suggestion/motivation for doing so would have been to provide improved system/method for managing user privacy across multiple online sites and applications and sharing data smoothly while maintaining security (Vandervort, paragraphs 05, 08, 09).
Therefore, it would have been obvious to combine Klare with Wechsler and Vandervort to obtain the invention as specified in claim 1.
Regarding claim 2, the combination of Klare, Wechsler and Vandervort discloses the method of claim 1, wherein the machine learning module comprises AT LEAST ONE OF:
a k-NN algorithm; a neural network (Wechsler, fig. 4 and paragraphs 22-24, wherein the machine learning module used is a convolutional neural network (CNN)); support vector machines (SVMs); logistic regression; naive Bayes; memory-based learning; random forests; bagged trees; decision trees; boosted trees; or boosted stumps.
Regarding claim 3, the combination of Klare, Wechsler and Vandervort discloses the method of claim 2, wherein the neural network comprises a convolutional neural network (CNN) (Wechsler, fig. 4 and paragraphs 22-24, wherein the machine learning module used is a convolutional neural network (CNN)).
Regarding claim 4, the combination of Klare, Wechsler and Vandervort discloses the method of claim 1, wherein obtaining the reference facial recognition data comprises:
downloading a plurality of images; and generating the reference facial recognition data based on the plurality of downloaded images (Klare, fig. 1, elements 104, 106; fig. 2; paragraphs 42, and 45-47, wherein a plurality of images are downloaded by a web crawler and the reference facial recognition data (i.e. feature vector) is generated therefrom by facial recognition algorithm (104)).
Regarding claim 5, the combination of Klare, Wechsler and Vandervort discloses the method of claim 1, wherein the identifying the one or more candidates that match the at least one face is further based on a scoring algorithm (paragraphs 69 and 70, wherein identifying candidates that match is determined based on a scoring algorithm based on a Euclidean distance similarity score/value).
Regarding claim 6, the combination of Klare, Wechsler and Vandervort discloses the method of claim 5, wherein the scoring algorithm is based on a distance value (paragraphs 69 and 70, wherein identifying candidates that match is determined based on a Euclidean distance similarity score/value).
Regarding claim 8, the combination of Klare, Wechsler and Vandervort discloses the method of claim 1, wherein the image received from the user device is captured by the user device, a network camera, or imported from a second user device (Klare, paragraphs 44, 48 and 54, wherein the image can be imported from a second user device indicated by its location (i.e. URL)).
Regarding claim 9, the combination of Klare, Wechsler and Vandervort discloses the method of claim 1, wherein the reference facial recognition data comprises one or more facial images downloaded by a web crawler (Klare, fig. 2; paragraphs 41, 42, and 45-47, wherein the reference data is generated from a plurality of facial images downloaded from the internet by a web crawler).
Regarding claim 10, the combination of Klare, Wechsler and Vandervort discloses the method of claim 1, wherein the reference facial recognition data comprises one or more facial images obtained from the Internet, professional websites, law enforcement websites, OR departments of motor vehicles (Klare, fig. 2; paragraphs 41, 42, and 45-47, wherein the reference data is generated from a plurality of facial images obtained from the internet by a web crawler).
Regarding claim 16, Klare discloses a method comprising:
sending, by a user device to a server, an image, wherein the image comprises at least one face of a subject (Fig. 1, elements 108, 110; Fig. 4; paragraphs 43-44, 48 and 54, wherein a query face image is provided by a user device to the search system server (108));
receiving, from the server, image source information associated with each of the one or more candidates, wherein the image source information comprises a link to an online webpage associated with the candidate (Fig. 1; Fig. 3; Fig. 4; paragraphs 42, 51-54, wherein when a match is determined candidate metadata, including source information (i.e. URL that identifies a source of the image corresponds to the link to an online profile associated with the candidate) associated with each matching candidate, is retrieved from the database/gallery by the search system server and sent to the user device (i.e. received by the user device)), wherein the one or more candidates are identified based on Fig. 3; Fig. 4; paragraphs 50, 51, 54, 69 and 70, wherein a vector derived from the query face image is compared to reference facial vectors derived from reference facial image by the search system server, and candidates with similar/matching faces are identified), each associated with a face of a plurality of faces from images obtained from one or more publicly accessible websites, stored in a database (Fig. 1, elements 102, 104, and 108; Fig. 2; paragraphs 41-43 and 45-47, wherein reference facial images are obtained via public or private sources (e.g. public URL) and a face recognition algorithm (104) generates the reference facial vector from the face in the reference image, and then the image, source (i.e. URL) and vector are stored in the gallery file/database);
receiving, based on the image source information an image of the one or more candidates, Fig. 1; Fig. 3; Fig. 4; paragraphs 42, 51-54, wherein the matched images are received, each based on the image originally scraped from URL that identifies its source, are transmitted back to the user’s device (i.e. received by the user device) for display).
Klare does not disclose expressly that comparing facial recognition data (i.e. vectors) is performed using a machine learning module or receiving, based on the image source information an image of the one or more candidates, based on a predetermined privacy setting of the identified candidate.
Wechsler discloses a process of comparing facial recognition data using a machine learning module to generate the facial recognition data in the form of feature vectors that are used for the comparison (Fig. 4; paragraphs 22-24).
Klare & Wechsler are combinable because they are from the same art of image processing, specifically facial image processing.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of comparing facial recognition data using a machine learning module to generate the facial recognition data in the form of feature vectors that are used for the comparison, as taught by Wechsler, into the process comparing query and reference facial recognition data disclosed by Klare.
The suggestion/motivation for doing so would have been to provide better recognition performance (Wechsler, paragraph 07).
Additionally, Vandervort discloses a process for receiving, based the source of information, other information associated with a candidate, based on a predetermined privacy setting of an identified candidate (Figs. 4, 5; paragraphs 10, 11, 48-50, wherein a candidate configures the privacy settings that regulate the information associated with them that can be retrieved).
Klare & Vandervort are combinable because they are from the same art of data retrieval associated with an individual.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of receiving, based the source of information, other information associated with a candidate, based on a predetermined privacy setting of an identified candidate, as taught by Vandervort, into the process of, receiving, based on the image source information an image of the one or more candidates disclosed by Klare.
The suggestion/motivation for doing so would have been to provide improved system/method for managing user privacy across multiple online sites and applications and sharing data smoothly while maintaining security (Vandervort, paragraphs 05, 08, 09).
Therefore, it would have been obvious to combine Klare with Wechsler and Vandervort to obtain the invention as specified in claim 16.
Regarding claim 17, the combination of Klare, Wechsler and Vandervort discloses the method of claim 16, further comprising: preprocessing, prior to sending the image to the server, the image (Wechsler, Fig. 4 and paragraph 22, wherein the input is preprocessed, including normalization of pose and image size, before sending to the machine learn CNN for feature extraction and comparison).
Regarding claim 18, the combination of Klare, Wechsler and Vandervort discloses the method of claim 17, wherein the preprocessing comprises at least one of cropping, resizing, gradation conversion, median filtering, histogram equalization, or size normalized image processing (Wechsler, Fig. 4 and paragraph 22, wherein the input is preprocessed, including normalization of pose and image size, before sending to the machine learn CNN for feature extraction and comparison).
Regarding claim 19, please refer to the rejection of claim 8 above.
Regarding claim 22, Klare discloses a system comprising:
a user device (Fig. 1, element 110, paragraph 44); and
a server (Fig. 1, elements 102 and 108; paragraphs 41-43, where the combination of search (108) and ingestion (102) systems corresponds to the broadest reasonable interpretation of a “server” in which a remote system or process is serving a client/user device through a network),
wherein the user device is configured to:
send, to the server, an image comprising at least one face of a subject (Fig. 1, element 110; Fig. 4; paragraphs 43-44, 48 and 54, wherein a query face image is provided by a user device and received by the search system); and
display an image associated with one or more candidates corresponding to the subject and image source information associated with each of the one or more candidates (Fig. 1; Fig. 3; Fig. 4; paragraphs 42, 51-54, 70, wherein the matched images (i.e. image associated with candidates that match the face of the subject/query image) and metadata such as source information (i.e. URL that identifies a source of the image) are transmitted back to the user’s device for display); and
wherein the server is configured to:
obtain, from one or more publicly accessible sites, reference facial recognition data, wherein the reference facial recognition data comprises a plurality of vector representations, each associated with one face of a plurality of faces (Fig. 1, elements 102 and 108; Fig. 2; paragraphs 41-43 and 45-47, where facial images are obtained via public or private sources (e.g. public URL) by the ingestion system (102) and a face recognition algorithm (104) generates reference facial recognition data from the face in the image in the form of feature vector representations for each);
store the reference facial recognition data and image source information associated with the facial recognition data in a database (Fig. 1, element 106; paragraph 42, wherein the reference facial recognition data (i.e. feature vector) and image source information (e.g. URL) are stored together in the gallery files database);
generate facial recognition data comprising a vector representation of the at least one face (Fig. 1, elements 110, 108, 104; Fig. 3; Fig. 5A-5C; paragraphs 48, 49, 67, wherein the query face image is transformed into a feature vector, corresponding to the facial recognition data, by the face recognition algorithm (104) of the search system portion of the server);
compare, Fig. 3; paragraphs 50, 51, 69 and 70, wherein the query facial recognition data/vectors are compared to reference facial recognition data/vectors by the search system of the “server”);
identify, based on a comparison of the facial recognition data to the reference facial recognition data, one or more candidates that match the at least one face (Fig. 3; Fig. 4; paragraphs 50, 51, 54, 69 and 70, wherein based on comparison of the vectors, candidates with similar/matching faces are identified);
based on identification of the one or more candidates matching the at least one face, retrieve, from the database, Fig. 1; Fig. 3; Fig. 4; paragraphs 42, 51-54, wherein when a match is determined candidate metadata such as source information (i.e. URL that identifies a source of the image corresponds to the link to an online profile associated with the candidate) is retrieved from the database/gallery); and
send, to the user device, an image of the one or more candidates and the image source information (Fig. 1; Fig. 3; Fig. 4; paragraphs 42, 51-54, wherein the matched images and metadata such as source information (i.e. URL that identifies a source of the image) are transmitted back to the user’s device for display).
Klare does not disclose expressly that comparing facial recognition data (i.e. vectors) is performed using a machine learning module, or based on identification of the one or more candidates matching the at least one face, retrieve, from the database, based on a predetermined privacy setting of the identified candidate, image source information.
Wechsler discloses a process of comparing facial recognition data using a machine learning module to generate the facial recognition data in the form of feature vectors that are used for the comparison (Fig. 4; paragraphs 22-24).
Klare & Wechsler are combinable because they are from the same art of image processing, specifically facial image processing.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of comparing facial recognition data using a machine learning module to generate the facial recognition data in the form of feature vectors that are used for the comparison, as taught by Wechsler, into the process comparing query and reference facial recognition data disclosed by Klare.
The suggestion/motivation for doing so would have been to provide better recognition performance (Wechsler, paragraph 07).
Additionally, Vandervort discloses a process for retrieving, from a database, based on a predetermined privacy setting of an identified candidate, information associated with the candidate (Figs. 4, 5; paragraphs 10, 11, 48-50, wherein a candidate configures the privacy settings that regulate the information associated with them that can be retrieved).
Klare & Vandervort are combinable because they are from the same art of data retrieval associated with an individual.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of retrieving, from a database, based on a predetermined privacy setting of an identified candidate, information associated with the candidate, as taught by Vandervort, into the process of, based on identification of the one or more candidates matching the at least one face, retrieving, from the database, image source information associated with each of the one or more candidates, wherein the image source information comprises a link to an online webpage associated with the one or more candidates disclosed by Klare.
The suggestion/motivation for doing so would have been to provide improved system/method for managing user privacy across multiple online sites and applications and sharing data smoothly while maintaining security (Vandervort, paragraphs 05, 08, 09).
Therefore, it would have been obvious to combine Klare with Wechsler and Vandervort to obtain the invention as specified in claim 22.
Regarding claim 23, please refer to the rejection of claims 17 and 18 above.
Regarding claims 24-26, please refer to the rejections of claims 4, 9 and 10, respectively, above.
Regarding claims 29 and 30, please refer to the rejections of claims 5 and 6, respectively, above.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over US 2016/0132720 to Klare et al. (“Klare”) in view of US 2018/0293429 to Wechsler et al. (“Wechsler”) and US 2014/0237610 to Vandervort, in further in view of US 2018/0101742 to Burge et al. (“Burge”).
As to claim 7, the combination of Klare, Wechsler and Vandervort discloses the method of claim 1.
The combination of Klare, Wechsler and Vandervort does not disclose expressly wherein the wherein the vector representation of the at least one face comprises a 512 point vector or 1024 point vector.
However, Burge discloses comparing by a server device the facial recognition data to reference facial recognition data associated with a plurality of stored facial images of individuals to identify at least one likely candidate matching the captured facial image (Fig. 3, Fig. 5B, elements 524-532, wherein the first binary vector is compared to the plurality of vectors stored in a database to determine a likely match), wherein the facial recognition data comprise a vector representation of the captured facial image of the subject and the reference facial recognition data comprise a vector representation of the stored facial image in the database (Fig. 3; Figs. 5a- 5b, elements 510-522; paragraphs 58, 70-93, wherein the image is transformed into a first binary vector corresponding to facial recognition data that is then compared with the plurality of vector representing stored facial images in the gallery files or databases) and wherein the vector representation of the captured facial image of the subject or the vector representation of the stored facial image in the database comprises a 512 point vector or a 1024 point vector (paragraph 76).
Klare, Wechsler, Vandervort & Burge are combinable because they are from the same art of facial image processing.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the use a vector representation of the captured or stored facial image that comprises a 512 point vector or 1024 point vector, as taught by Burge, into the process of using facial recognition for providing information about a subject disclosed by the combination of Klare, Wechsler and Vandervort.
The suggestion/motivation for doing so would have been to provide time efficient comparison (Burge, paragraph 05).
Therefore, it would have been obvious to combine Klare, Wechsler and Vandervort with Burge to obtain the invention as specified in claim 7.
Claims 11 and 27 are rejected under 35 U.S.C. 103 as being unpatentable over US 2016/0132720 to Klare et al. (“Klare”) in view of US 2018/0293429 to Wechsler et al. (“Wechsler”) and US 2014/0237610 to Vandervort, in further in view of US 2014/0294257 to Tussy.
As to claim 11, the combination of Klare, Wechsler and Vandervort discloses the method of claim 1.
The combination of Klare, Wechsler and Vandervort does not disclose expressly wherein the database comprises a plurality of criminal records associated with the reference facial recognition data.
Tussy discloses a process that includes capturing a facial image by a user device, sending the image to a server for comparison with images in a database, wherein the database also comprises criminal records associated with the stored facial images (paragraphs 85, 86, 110 and 117).
Klare, Wechsler, Vandervort & Tussy are combinable because they are from the same art of facial image processing.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of associating a facial image with criminal records in a database, as taught by Tussy, into the process of using facial recognition for providing information about a subject disclosed by the combination of Klare, Wechsler and Vandervort.
The suggestion/motivation for doing so would have been to alert a user of a potentially dangerous individual (Tussy, paragraphs 86 and 110).
Therefore, it would have been obvious to combine Klare, Wechsler and Vandervort with Tussy to obtain the invention as specified in claim 11.
Claim 27 is rejected for the same reasons and logic disclosed above with regards to claim 11.
Claims 12, 15, 20 and 28 rejected under 35 U.S.C. 103 as being unpatentable over US 2016/0132720 to Klare et al. (“Klare”) in view of US 2018/0293429 to Wechsler et al. (“Wechsler”) and US 2014/0237610 to Vandervort, in further view of US 2019/0354750 to Nazemi et al. (“Nazemi”).
As to claim 12, the combination of Klare, Wechsler and Vandervort discloses the method of claim 1.
The combination of Klare, Wechsler and Vandervort does not disclose expressly sending a notification to the user device if a first candidate, of the one or more candidates, poses a high risk to the public or is a criminal.
Nazemi discloses a process that includes capturing a facial image by a user device, sending the image to a central server for comparison with images in a database and transmitting back information/notification to the user device if the identified candidate poses a high risk to public (paragraphs 02, 07, 27).
Klare, Wechsler, Vandervort & Nazemi are combinable because they are from the same art of facial image processing.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of transmitting a notification back to a user device if an identified candidate poses a high risk to the public, as taught by Nazemi, into the process of providing information about a subject disclosed by the combination of Klare, Wechsler and Vandervort.
The suggestion/motivation for doing so would have been to provide swift automated facial recognition in high traffic queues (Nazemi, paragraph 02).
Therefore, it would have been obvious to combine Klare, Wechsler and Vandervort with Nazemi to obtain the invention as specified in claim 12.
Claims 20 and 28 are rejected for the same reasons and logic disclosed above with regards to claim 12 above.
As to claim 15, the combination of Klare, Wechsler and Vandervort discloses the method of claim 1.
The combination of Klare, Wechsler and Vandervort does not disclose expressly providing access to the database to a plurality of users.
Nazemi discloses a process that includes providing access to a plurality of officers/user, to a central server and database of reference facial images (fig 1, paragraphs 24-28).
Klare, Wechsler, Vandervort & Nazemi are combinable because they are from the same art of facial image processing.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of providing access to a database to a plurality of users, as taught by Nazemi, into the process of providing information about a subject disclosed by the combination of Klare, Wechsler and Vandervort.
The suggestion/motivation for doing so would have been to provide swift automated facial recognition in high traffic queues for determining if an individual should be granted access into the country (Nazemi, paragraph 02).
Therefore, it would have been obvious to combine Klare, Wechsler and Vandervort with Nazemi to obtain the invention as specified in claim 15.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over US 2016/0132720 to Klare et al. (“Klare”) in view of US 2018/0293429 to Wechsler et al. (“Wechsler”) and US 2014/0237610 to Vandervort, in further view of US 2016/0196467 to Xia.
As to claim 13, the combination of Klare, Wechsler and Vandervort discloses the method of claim 1.
The combination of Klare, Wechsler and Vandervort does not disclose expressly the image comprises a three-dimensional facial image of the subject.
Xia discloses a process of 3D facial image recognition (Figs. 1 and 2).
Klare, Wechsler, Vandervort & Xia are combinable because they are from the same art of facial image processing.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of using 3D images of a subjects face for facial identification, as taught by Xia, in to the process for using facial recognition to acquire/provide information about a subject as disclosed by the combination of Klare, Wechsler and Vandervort.
The suggestion/motivation for doing so would have been to use a 3D facial image, as opposed to a 2D facial image, that provides the advantage not being seriously affected by illumination robustness, gestures and expressions (Xia, paragraph 05).
Therefore, it would have been obvious to combine Klare, Wechsler and Vandervort with Xia to obtain the invention as specified in claim 13.
Claims 14 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over US 2016/0132720 to Klare et al. (“Klare”) in view of US 2018/0293429 to Wechsler et al. (“Wechsler”) and US 2014/0237610 to Vandervort, in further in view of US 2012/0054691 to Nurmi.
As to claim 14, the combination of Klare, Wechsler and Vandervort discloses the method of claim 1.
The combination of Klare, Wechsler and Vandervort does not disclose expressly wherein the image comprises a second face, wherein the method further comprises identifying a relation between the subject and the second subject.
Nurmi discloses a process for performing facial recognition on a facial image that contains facial images of multiple subjects (Nurmi, paragraph 42) and identifying a relation between two or more 15subjects having facial images captured in a single image (Nurmi, Fig. 7, paragraphs 52, 54, 72, 82 and 83).
Klare, Wechsler, Vandervort & Nurmi are combinable because they are from the same art of facial image processing.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of performing facial recognition on a facial image that contains facial images of multiple subjects and identifying a relation between two or more subjects in the image, as taught by Nurmi, into the process of using facial recognition for providing information about a subject disclosed by the combination of Klare, Wechsler and Vandervort.
The suggestion/motivation for doing so would have been to provide a user-friendly, efficient and reliable manner in which to determine common friend of individual (Nurmi, paragraph 08).
Therefore, it would have been obvious to combine Klare, Wechsler and Vandervort with Nurmi to obtain the invention as specified in claim 14.
Claim 21 is rejected for the same reasons and logic disclosed above with regards to claim 14 above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See attached PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AARON W CARTER whose telephone number is (571)272-7445. The examiner can normally be reached 8am - 5pm (Mon - Fri).
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/AARON W CARTER/Primary Examiner, Art Unit 2661