Prosecution Insights
Last updated: April 19, 2026
Application No. 18/604,868

System and Method for Detecting Potential Matches Between a Candidate Biometric and a Dataset of Biometrics

Non-Final OA §101§103§DP
Filed
Mar 14, 2024
Examiner
CHANNAVAJJALA, SRIRAMA T
Art Unit
2154
Tech Center
2100 — Computer Architecture & Software
Assignee
Aeva, Inc.
OA Round
3 (Non-Final)
75%
Grant Probability
Favorable
3-4
OA Rounds
3y 5m
To Grant
99%
With Interview

Examiner Intelligence

Grants 75% — above average
75%
Career Allow Rate
518 granted / 690 resolved
+20.1% vs TC avg
Strong +33% interview lift
Without
With
+32.6%
Interview Lift
resolved cases with interview
Typical timeline
3y 5m
Avg Prosecution
24 currently pending
Career history
714
Total Applications
across all art units

Statute-Specific Performance

§101
19.6%
-20.4% vs TC avg
§103
37.0%
-3.0% vs TC avg
§102
14.8%
-25.2% vs TC avg
§112
9.7%
-30.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 690 resolved cases

Office Action

§101 §103 §DP
Notice of Pre-AIA or AIA Status The present application 18/604,868, filed on 11/18/2024 (or after March 16, 2013), is being examined under the first inventor to file provisions of the AIA (First Inventor to File). 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. This application is a CON of 18/224,238 filed on 07/20/2023 ABN 18/224,238 is a CON of 16/752,634 filed on 01/25/2020 is now US PAT 11710297 16/752,634 is a CON of 14/667,925 filed on 03/25/2015 is now US PAT 10546215 14/667,925 has DOM PRO 61/972,366 filed on 03/30/2014 DETAILED ACTION Response to RCE Claims 1-42 are cancelled, new claims 43-62 pending in this application. Examiner acknowledges applicant’s amendment filed on 3/10/2026 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 3/10/2026 has been entered Examiner acknowledges applicant’s preliminary amendment filed on 11/18/2024 Drawings The Drawings filed on 3/14/2024 are acceptable for examination purpose. Priority Acknowledgment is made of applicant’s claim for domestic priority application U.S. Provisional Patent application serial number # 61/972,366 filed on 03/30/2014 under 35 U.S.C. 119 (e) Response to Arguments Applicant's arguments filed 3/10/2026 with respect to claim 43-62 have been fully considered but they are not persuasive, for examiner’s response, see discussion below: a)At page 8, Applicant’s arguments with respect to cancelled claim(s) 23-42 under 35 USC 101 have been considered but are moot, however, new claims 43-62 are rejected under 35 USC 101 b)At page 8, examiner noted applicant’s remarks on double patent rejection, however, new claims 43-62 are rejected under nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 11,710,297 c) At page 8-9, Applicant’s arguments with respect to cancelled claim(s) 23-42 have been considered but are moot, however the new claims 43-62 are rejected Boult, US Pub. No. 2011/0106734 in view of Mitura et al., US Pub. No. 2013/0148898, Liu et al.,, US Pub. No.2008/0275862 Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 43-62 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The judicial exception is not integrated into a practical application. Claim 43,53 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The eligibility analysis in support of these findings is provided below, in accordance with the 2019 Revised Patent Subject Matter Eligibility Guidance, hereinafter 2019 PEG Step 1. In accordance with Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is noted that the method of claim 43,53, directed to one of the eligible categories of subject matter and therefore satisfy Step 1. Step 2A. In accordance with Step 2A prong one of the 2019 PEG, the limitations reciting the abstract idea are highlighted, and the limitations directed to additional elements are highlighted, as set forth in exemplary claim 43 Claim 1-22. Canceled Claim 23-42. Cancel “A method for detecting a potential match between a probe and a plurality of entries in a dataset, wherein each entry in the dataset comprises a plurality of gallery images, wherein the probe comprises a plurality of probe images, the method comprising: for each respective entry in the dataset: spectrally clustering, by a computing platform, the plurality of probe images of the probe and the plurality of gallery images of the respective entry, wherein the spectral clustering is constrained to only two outcomes: a first outcome when the plurality of probe images of the probe and the plurality of gallery images of the respective entry collectively correspond to one cluster and a second outcome when the plurality of probe images of the probe and the plurality of gallery images of the respective entry collectively correspond to two clusters, when the outcome of the spectral clustering is the first outcome: identifying, via the computing platform, the probe and the respective entry as a match, and adding the plurality of probe images of the probe to the plurality of gallery images of the respective entry; and when the outcome of the spectral clustering is the second outcome for each of the identifying, via the computing platform, the probe as unique in the dataset, and adding the probe as a new entry in the dataset”, The limitations of claim 42 above, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example potential match between a probe and a plurality of entries in a dataset, in the context of this claim encompasses the user thinking mere collection of data, adding as new entry of the dataset The limitation “spectrally clustering……… …………………..spectral clustering is constrained to only two outcomes”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example, in the context of this claim, this limitation encompasses the user thinking of collection of images in a cluster. when the outcome of the spectral clustering is the second outcome for each of the identifying, via the computing platform, the probe as unique in the dataset, and adding the probe as a new entry in the dataset”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example, in the context of this claim, this limitation encompasses the user thinking mere collection of data, adding data If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas set forth in the 2019 PEG. Accordingly, the claim recites an abstract idea. With respect to Step 2A prong two of the 2019 PEG, the judicial exception is not integrated into a practical application. The additional elements are directed to method steps, however, these elements fail to integrate the abstract idea into a practical application because they fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular data structure of gallery images collect(ion) that identify particular match, to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. Furthermore, although these elements have been fully considered, they are directed to the use of generic computing elements (para 18, 26-31, of the instant specification make it clear that the disclosed functionality is implemented on well-known computing systems and general purpose computing devices) to perform the abstract idea, which is not sufficient to amount to a practical application (as noted in the 2019 PEG) and is tantamount to simply saying "apply it" using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment (computer based operating environment) by using the computer as a tool to perform the abstract idea. Since the analysis of Step 2A prong one and prong two results in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception. Step 2B. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional method limitations are directed to a generic computer, at a very high level of generality and without imposing meaningful limitations on the scope of the claim. In addition para: 8, 26-31 of the instant specification describe generic off-the-shelf computer-based elements for implementing the claimed invention which does not amount to significantly more than the abstract idea and is not enough to transform an abstract idea into eligible subject matter. Such generic, high-level, and nominal involvement of a computer or computer-based elements for carrying out the invention merely serves to tie the abstract idea to a particular technological environment, which is not enough to render the claims patent-eligible, as noted at pg. 74624 of Federal Register/Vol. 79, No. 241, citing Alice, which in turn cites Mayo. Further, See, e.g., Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94 (Fed. Cir. 2015) ("Just as Diehr could not save the claims in Alice, which were directed to 'implement[ing] the abstract idea of intermediated settlement on a generic computer', it cannot save O/P's claims directed to implementing the abstract idea of price optimization on a generic computer.") (citations omitted). See also, Affinity Labs of Texas LLC v. DirecTV LLC, 838 F.3d 1253, 1257-1258 (Fed. Cir. 2016) (mere recitation of a GUI does not make a claim patent-eligible); Intellectual Ventures I LLC v. Capital One Bank, 792 F.3d 1363, 1370 (Fed. Cir. 2015) ("the interactive interface limitation is a generic computer element".) The additional elements are broadly applied to the abstract idea at a high level of generality ("similar to how the recitation of the computer in the claims in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer,") as explained in MPEP § 2106.05(f)) and they operate in a well-understood, routine, and conventional manner. MPEP § 2106.05 (d)(II) sets forth the following: The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g. at a high level of generality) as insignificant extra-solution activity. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec...; TLI Communications LLC v. AV Auto. LLC...; OIP Techs., Inc., v. Amazon.com, Inc... ; buySAFE, Inc. v. Google, Inc...; Performing repetitive calculations, Flook ... ; Bancorp Services v. Sun Life...; Electronic recordkeeping, Alice Corp...; Ultramercial... ; Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc...; Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank...; and A web browser's back and forward button functionality, Internet Patent Corp. v. Active Network, Inc... Courts have held computer-implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking). Examiner rejected claim 53 in the analysis of claim 43, and claim 53 is rejected on that basis. Claim 44,54,calculation step(s): “forming an adjacency matrix of biometric scores of a size (N1 + N2) by (N1 + N2), wherein N1 is a number of probe images and wherein N2 is a number of gallery images, determining a graph Laplacian based on the adjacency matrix, determining an eigenspace decomposition, including eigenvalues and eigenvectors, based on the graph Laplacian, and estimating a number of clusters based on the eigenspace”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer component(s) such as by the processor. That is, other than reciting “by a processor”, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “by a processor”, “biometric scores of a size (N1 + N2) by (N1 + N2)” in the context of this claim limitation encompasses the user manually calculating the matching score, i.e., claim limitation recites a mathematical operation of biometric scores is an abstract idea, See MPEP 2106.04, subsection II (i.e., mathematical concepts). Similarly, the limitation of “determining a graph Laplacian based on the adjacency matrix”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components and using mere formula in the context of this claim encompasses the user thinking that the most-used eigenvalues and eigenvectors, If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “mental processes” grouping of abstract ideas. Accordingly, the claim 24 recites an abstract idea, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 45. (New) The method of claim 43, wherein spectrally clustering the plurality of probe images and the plurality of gallery images comprises: assigning each of the plurality of probe images to an individual vertex in a graph; assigning each of the plurality of gallery images to an individual vertex in the graph; and determining a similarity score for each pair of vertices in the graph”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.. claim 46. (New) The method of claim 44, wherein determining a graph Laplacian comprises: determining the graph Laplacian as L = D – W”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer component(s) such as by the processor. That is, other than reciting “by a processor”, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “by a processor”, “determining the graph Laplacian as L = D—W”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components and using mere formula in the context of this claim encompasses the user thinking that the most-used graph Laplacian as L = D—W (formula). The claim limitation recites a mathematical operation of biometric scores is an abstract idea, See MPEP 2106.04, subsection II (i.e., mathematical concepts). If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “mental processes” grouping of abstract ideas. Accordingly, the claim 26 recites an abstract idea, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 47. (New) The method of claim 44, “wherein determining a graph Laplacian comprises: determining the graph Laplacian as L = / - D-1W”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer component(s) such as by the processor. That is, other than reciting “by a processor”, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “by a processor” graph Laplacian as “, PNG media_image1.png 25 96 media_image1.png Greyscale (formula). The claim limitation recites a mathematical operation of biometric scores is an abstract idea, See MPEP 2106.04, subsection II (i.e., mathematical concepts). If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “mental processes” grouping of abstract ideas. Accordingly, the claim 27 recites an abstract idea, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 48. (New) The method of claim 44, “wherein determining a graph Laplacian comprises: determining the graph Laplacian as L = /-D-1/2WD-1/2 “, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer component(s) such as by the processor. That is, other than reciting “by a processor”, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “by a processor”, “graph Laplacian as PNG media_image2.png 28 136 media_image2.png Greyscale , (formula). The claim limitation recites a mathematical operation of biometric scores is an abstract idea, See MPEP 2106.04, subsection II (i.e., mathematical concepts). If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “mental processes” grouping of abstract ideas. Accordingly, the claim 27 recites an abstract idea, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 49. (New) The method of claim 43, “wherein estimating a number of clusters comprises: comparing the eigenvalues or function thereof against a threshold”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 50. (New) The method of claim 49, “wherein the threshold is a negative number”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 51. (New) The method of claim 44, “wherein forming an adjacency matrix comprises: determining a similarity score between one of the plurality of probe images and one of the plurality of gallery images”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. claim 52. (New) The method of claim 44, “wherein forming an adjacency matrix comprises: determining a similarity score between each pair of images in a set of images comprised of the plurality of probe images and the plurality of gallery images”, claim 55. (New) The method of claim 53, “wherein the plurality of probe biometrics comprises a first biometric type and a second biometric type, wherein the plurality of gallery biometrics comprises the first biometric type and the second biometric type, and wherein the first biometric type and the second biometric type are different from one another”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 56. (New) The method of claim 53, “wherein the plurality of probe biometrics comprises biometric representations of a processed image, a fingerprint, a palmprint, an iris scan, a 3D mesh, a genetic sequence, a heartbeat, a gait or a speech component”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 57. (New) The method of claim 53, “wherein the plurality of probe biometrics is divided into separate homogeneous biometrics, the spectral clustering is performed for each biometric, and the results are combined”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 58. (New) The method of claim 57, “wherein the combination is done in the eigenspace for each biometric or related component”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 59. (New) The method of claim 57, “wherein the combination is done with a combination of the separate adjacency matrices for each biometric or related component”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 60. (New) The method of claim 57, “wherein the combination is done on the resulting clusters, or a function of the clusters, for each biometric or related component”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 61. (New) The method of claim 43, “wherein spectrally clustering is constrained to only two outcomes by evaluating a hypothesis test with only two hypotheses including a first hypothesis that the plurality of probe images and the plurality of gallery images collectively correspond to one cluster, and a second hypothesis that the plurality of probe images and the plurality of gallery images collectively correspond to two clusters”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 62. (New) The method of claim 53, “wherein spectrally clustering is constrained to only two outcomes by evaluating a hypothesis test with only two hypotheses including a first hypothesis that the plurality of probe biometrics and the plurality of gallery biometrics collectively correspond to one cluster, and a second hypothesis that the plurality of probe biometrics and the plurality of gallery biometrics collectively correspond to two clusters”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. 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 claims at issue 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); and 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 a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The USPTO internet Web site contains terminal disclaimer forms which may be used. Please visit http://www.uspto.gov/forms/. The filing date of the application will determine what form 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 http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp. Claims 43-62 of US Application No. 18/604,868 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 11,710,297. Although the claims at issue are not identical, they are not patentably distinct from each other because the patented claims perform the same steps as the claims in the instant application. Instant US application: 18/604,868 US Patent No. 11,710,297 Claim 43,53, A method for detecting a potential match between a probe and a plurality of entries in a dataset, wherein each entry in the dataset comprises a plurality of gallery images, wherein the probe comprises a plurality of probe images, the method comprising: for each respective entry in the dataset: spectrally clustering, by a computing platform, the plurality of probe images of the probe and the plurality of gallery images of the respective entry, wherein the spectral clustering is constrained to only two outcomes: a first outcome when the plurality of probe images of the probe and the plurality of gallery images of the respective entry collectively correspond to one cluster and a second outcome when the plurality of probe images of the probe and the plurality of gallery images of the respective entry collectively correspond to two clusters, when the outcome of the spectral clustering is the first outcome: identifying, via the computing platform, the probe and the respective entry as a match, and adding the plurality of probe images of the probe to the plurality of gallery images of the respective entry; and when the outcome of the spectral clustering is the second outcome for each of the identifying, via the computing platform, the probe as unique in the dataset, and adding the probe as a new entry in the dataset claim 44,54 claim 45 claim 46 claim 47 claim 48 claim 52 Claim 1, 14, A method for detecting a potential match between a probe and a plurality of entries in a dataset, wherein each entry in the dataset comprises a plurality of gallery images, the method comprising: receiving the probe by a computing platform, the probe comprising a plurality of probe images; for each respective entry in the dataset: spectrally clustering, via the computing platform, the plurality of probe images and the plurality of gallery images of the respective entry to determine whether the plurality of probe images and the plurality of gallery images collectively correspond to one cluster or two clusters by evaluating a hypothesis test with only two hypotheses including a first hypothesis that the plurality of probe images and the plurality of gallery images collectively correspond to one cluster, and a second hypothesis that the plurality of probe images and the plurality of gallery images collectively correspond to two clusters, when the plurality of probe images and the plurality of gallery images collectively correspond to one cluster, identifying the probe and the respective entry as a match in the dataset, and when the plurality of probe images and the plurality of gallery images collectively correspond to two clusters, identifying the probe as unique in the dataset. Claim 2 Claim 3 Claim 4 Claim 5 Claim 6 Claim 8 It would have been obvious to a person of ordinary skill was made to modify and/or to omit the additional elements of claim 1-20 of U.S. Patent No. 11,710,297 to arrive at the claims 43-62 of the instant application 18/604,868 because the ordinary skilled person would have realized that the remaining element(s) would perform the same function as before and the only difference particularly claim 43,53 instant application 18/604,868 spectrally clustering, by a computing platform, the plurality of probe images of the probe and the plurality of gallery images of the respective entry, wherein the spectral clustering is constrained to only two outcomes: a first outcome when the plurality of probe images of the probe and the plurality of gallery images of the respective entry collectively correspond to one cluster and a second outcome when the plurality of probe images of the probe and the plurality of gallery images of the respective entry collectively correspond to two clusters while claim 1 of U.S. Patent No. 11,710,297, spectrally clustering, via the computing platform, the plurality of probe images and the plurality of gallery images of the respective entry to determine whether the plurality of probe images and the plurality of gallery images collectively correspond to one cluster or two clusters by evaluating a hypothesis test with only two hypotheses including a first hypothesis that the plurality of probe images and the plurality of gallery images collectively correspond to one cluster, and a second hypothesis that the plurality of probe images and the plurality of gallery images collectively correspond to two clusters, particularly bold highlighted limitation(s) is/are absent of the limitation from instant application 18/604,868 claim 43,53 Omission and/or addition of elements and its function in combination is obvious expedient if the remaining elements perform same functions as before, as such instant application claim 23,33 are broader It would have been obvious to a person of ordinary skill in the art at the time the invention was made to modify, add or omit the additional elements of claims 1, 14 to arrive at the claims 43,53 of the instant application because the person would have realized that the remaining element would perform the same functions as before. "Omission of element and its function in combination is obvious expedient if the remaining elements perform same functions as before." See In re Karlson (CCPA) 136 USPQ 184, decide Jan 16, 1963, Appl. No. 6857, U. S. Court of Customs and Patent Appeals. 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. The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. Claims 43, 53, 55-57, 59-62 is/are rejected under 35 U.S.C. 103 as being unpatentable over Boult et al., (hereafter Boult), US Pub. No. 2011/0106734 published May, 2011 in view of Mitura et al., (hereafter Mitura), US Pub. No. 2013/0148898 published Jun, 2013 Claim 1-22. Canceled Claim 23-42. Cancel As to claim 43, Boult teaches a system which including “A method for detecting a potential match between a probe and a plurality of entries in a dataset, wherein each entry in the dataset comprises a plurality of gallery images, wherein the probe comprises a plurality of probe images, the method comprising: (Boult: fig 1-2, 0015,0046 - Boult teaches probe sample element 130 and the recognition gallery data compare for possible score match of the data set(s) PNG media_image3.png 192 211 media_image3.png Greyscale PNG media_image4.png 171 199 media_image4.png Greyscale for each respective entry in the dataset: (Boult : fig 2, probe samples) “spectrally clustering, by a computing platform”, (Boult : fig 3, element 220 and element 240 – Boult teaches machine learning associated with the training probe sample(s) assessment and predicting similarities of data samples) the plurality of probe images of the probe and the plurality of gallery images of the respective entry, (Boult: fig 2, element 130, element 110, 0016 – Boult teaches both probe sample and the image gallery) wherein the spectral clustering is constrained to only two outcomes (Boult: fig 3, element 240, 270 – Boult teaches respective probe samples classified using machine learning): “a first outcome when the plurality of probe images of the probe and the plurality of gallery images of the respective entry collectively correspond to one cluster and a second outcome when the plurality of probe images of the probe (Boult: fig 2-3, 0046-0047 – Boult teaches both probe sample data cluster and the recognition gallery in analyzing and predicting respective statistical analyzed data) and when the outcome of the spectral clustering is the first outcome (Boult: fig 3 – Boult teaches machine learning classifier of respective recognition gallery and probe samples entry collection corresponds to probe samples): “identifying, via the computing platform, the probe and the respective entry as a match” (Boult: fig 2-3, 0046 – Boult teaches probe sample(s) as training probe sample sent to train machine learning computing platform, probe samples are compared and/or matched with recognition gallery data) and “adding the plurality of probe images of the probe to the plurality of gallery images of the respective entry” (Boult: fig 1-2, 1011,0046 – Boult teaches acquiring more data to the probe samples in order to in order to predict and normalize the data); PNG media_image5.png 109 349 media_image5.png Greyscale and “when the outcome of the spectral clustering is the second outcome for each of the identifying, via the computing platform, (Boult : fig 3, element 220 and element 240) the probe as unique in the dataset, and adding the probe as a new entry in the dataset” (Boult: fig 1-2, each iteration of compare step unique probe sample and from the plurality of enrollment samples adding to the overall deriving scores, statistical value(s). It is however, noted that Boult does not disclose “the plurality of gallery images of the respective entry collectively corresponds to two clusters”, although Boult teaches probe sample database and recognition gallery (Boult: fig 2). On the other hand, Mitura disclosed the plurality of gallery images of the respective entry collectively corresponds to two clusters” (Mitura: Abstract, fig 2,3A, 0033-0034,0037,0043-0044 – Mitura teaches cluster database element 216 that stores multiple clusters where facial image(s) are stored in each clusters such as cluster 1, cluster 2……cluster N corresponds to gallery images and/or facial image(s) stored in the cluster DB element 216) PNG media_image6.png 212 162 media_image6.png Greyscale PNG media_image7.png 161 200 media_image7.png Greyscale It would have been obvious to a person of ordinary skill in the art at the time of filing the claimed invention clustering objects detected in video particularly facial images representing similar objects of Mitura et al., into prediction and fusion in classification of similarity scores of the objects such as probe samples and recognition gallery to produce biometric or images of Boult et al., because both Boult and Mitura supports objects of biometric, probe data and compare it with other cluster sample objects (Boult: Abstract, fig 1-2; Mitura: Abstract, 0038-0039). it would have been obvious to one skill ed in the art to substitute and/or modify one method for the other to use multiple clusters with respect to defining samples to analyze, compare clustered images to determine similarities of the facial images, times or locations of appearance (Mitura: 0023-0024), thereby improves overall quality and reliability of processing computational complexity of specific selected samples and/or segments of the objects As to claim 53, Boult teaches a system which including “A method for detecting a potential match between a probe and a plurality of entries in a dataset, wherein each entry in the dataset comprises a plurality of gallery biometrics, wherein the probe comprises a plurality of probe biometrics, the method comprising: (Boult: fig 1-2, 0015,0046 - Boult teaches probe biometric sample element 130 and the recognition gallery data compare for possible score match of the data set(s) PNG media_image3.png 192 211 media_image3.png Greyscale PNG media_image4.png 171 199 media_image4.png Greyscale for each respective entry in the dataset: (Boult : fig 2, probe biometric samples) “spectrally clustering, by a computing platform”, (Boult : fig 3, element 220 and element 240 – Boult teaches machine learning associated with the training probe sample(s) assessment and predicting similarities of data samples) the plurality of probe biometrics of the probe and the plurality of gallery biometrics of the respective entry, (Boult: fig 2, element 130, element 110, 0016 – Boult teaches both probe biometric sample and the gallery biometrics) wherein the spectral clustering is constrained to only two outcomes (Boult: fig 3, element 240, 270 – Boult teaches respective probe samples classified using machine learning): “a first outcome when the plurality of probe biometrics of the probe and the plurality of gallery biometrics of the respective entry collectively correspond to one cluster and a second outcome when the plurality of probe biometrics of the probe (Boult: fig 2-3, 0046-0047 – Boult teaches both probe biometricssample data cluster and the recognition gallery in analyzing and predicting respective statistical analyzed data) and when the outcome of the spectral clustering is the first outcome (Boult: fig 3 – Boult teaches machine learning classifier of respective recognition gallery and probe samples entry collection corresponds to probe samples): “identifying, via the computing platform, the probe and the respective entry as a match” (Boult: fig 2-3, 0046 – Boult teaches probe sample(s) as training probe sample sent to train machine learning computing platform, probe samples are compared and/or matched with recognition gallery data) and “adding the plurality of probe biometrics of the probe to the plurality of gallery biometrics of the respective entry” (Boult: fig 1-2, 1011,0046 – Boult teaches acquiring more data to the probe biometricssamples in order to in order to predict and normalize the data); PNG media_image5.png 109 349 media_image5.png Greyscale and “when the outcome of the spectral clustering is the second outcome for each of the identifying, via the computing platform, (Boult : fig 3, element 220 and element 240) the probe as unique in the dataset, and adding the probe as a new entry in the dataset” (Boult: fig 1-2, each iteration of compare step unique probe sample and from the plurality of enrollment samples adding to the overall deriving scores, statistical value(s). It is however, noted that Boult does not disclose “the plurality of gallery biometrics of the respective entry collectively corresponds to two clusters”, although Boult teaches probe sample database and recognition gallery (Boult: fig 2). On the other hand, Mitura disclosed “the plurality of gallery biometrics of the respective entry collectively corresponds to two clusters” (Mitura: Abstract, fig 2,3A, 0033-0034,0037,0043-0044 – Mitura teaches cluster database element 216 that stores multiple clusters where facial image(s) are stored in each clusters such as cluster 1, cluster 2……cluster N corresponds to gallery images and/or facial image(s) stored in the cluster DB element 216) PNG media_image6.png 212 162 media_image6.png Greyscale PNG media_image7.png 161 200 media_image7.png Greyscale It would have been obvious to a person of ordinary skill in the art at the time of filing the claimed invention clustering objects detected in video particularly facial images representing similar objects of Mitura et al., into prediction and fusion in classification of similarity scores of the objects such as probe samples and recognition gallery to produce biometric or images of Boult et al., because both Boult and Mitura supports objects of biometric, probe data and compare it with other cluster sample objects (Boult: Abstract, fig 1-2; Mitura: Abstract, 0038-0039). it would have been obvious to one skill ed in the art to substitute and/or modify one method for the other to use multiple clusters with respect to defining samples to analyze, compare clustered images to determine similarities of the facial images, times or locations of appearance (Mitura: 0023-0024), thereby improves overall quality and reliability of processing computational complexity of specific selected samples and/or segments of the objects As to claim 55, the combination of Boult, Mitura disclosed wherein the plurality of probe biometrics comprises a first biometric type and a second biometric type, wherein the plurality of gallery biometrics comprises the first biometric type and the second biometric type, and wherein the first biometric type and the second biometric type are different from one another” (Boult: 0046, 0049-0050) As to claim 56, the combination of Boult, Mitura disclosed ”wherein the plurality of probe biometrics comprises biometric representations of a processed image, a fingerprint, a palmprint, an iris scan, a 3D mesh, a genetic sequence, a heartbeat, a gait or a speech component” (Boult: 0049-0050). As to claim 57, the combination of Boult, Mitura “wherein the plurality of probe biometrics is divided into separate homogeneous biometrics, the spectral clustering is performed for each biometric, and the results are combined” (Boult: fig 2-3, 0046-0048). As to claim 59, the combination of Boult, Mitura “wherein the combination is done with a combination of the separate adjacency matrices for each biometric or related component” (Boult: 0055-0056). As to claim 60, the combination of Boult, Mitura “wherein the combination is done on the resulting clusters, or a function of the clusters, for each biometric or related component” (Boult: 0023-0025,0045-0046) As to claim 61-62, the combination of Boult, Mitura disclosed “wherein spectrally clustering is constrained to only two outcomes by evaluating a hypothesis test with only two hypotheses including a first hypothesis that the plurality of probe images (Boult: fig 2-3, fig 7-8, 0070-0072) and the plurality of gallery images collectively correspond to one cluster, and a second hypothesis that the plurality of probe images and the plurality of gallery images collectively correspond to two clusters” (Mitura: fig 2-3, 0043-0046). Claims 44-52,54,58 is/are rejected under 35 U.S.C. 103 as being unpatentable over Boult et al., (hereafter Boult), US Pub. No. 2011/0106734 published May, 2011 Mitura et al., (hereafter Mitura), US Pub. No. 2013/0148898 published Jun, 2013 in view of Liu et al., (hereafter Liu), US Pub. No.2008/0275862 published Nov, 2008. As to claim 44, 54, the combination of Boult, Mitura disclosed computing similarity probe sample scores (Boult: fig 2-3). “forming an adjacency matrix of biometric scores of a size (N1 + N2) by (N1 + N2), wherein N1 is a number of probe images and wherein N2 is a number of gallery images”(Boult: fig 2-3, fig 6, 0015, 0046-0047) However, both Boult, Mitura do not disclose “determining a graph Laplacian based on the adjacency matrix, determining an eigenspace decomposition, including eigenvalues and eigenvectors, based on the graph Laplacian and estimating a number of clusters based on the eigenspace”. On the other hand, Liu disclosed “determining a graph Laplacian based on the adjacency matrix, determining an eigenspace decomposition, including eigenvalues and eigenvectors, based on the graph Laplacian (Liu: 0006); “estimating a number of clusters based on the eigenspace” (Liu: fig 2, 0032), PNG media_image8.png 619 177 media_image8.png Greyscale It would have been obvious to a person of ordinary skill in the art at the time of filing the claimed invention spectral clustering of images using sequential matrix compression of Liu et al., into prediction and fusion in classification of similarity scores of the objects such as probe samples and recognition gallery to produce biometric or images of Boult et al., and clustering objects detected in video particularly facial images representing similar objects of Mitura et al, because all the prior arts of Boult, Mitura and Liu teaches clustering of images (Boult: fig 1-3; Mitura; fig 3A and Liu: 0004), it would have been obvious to one skill ed in the art to substitute and/or modify one method for the other to use clustering techniques particularly spectral clustering technique of Liu (0005) to achieve the predictable representation of image objects to be clustered and relationship between images objects as a graph, where relationship represents the similarity between image objects (Liu: 0005-0006), while spectral clustering allows training probe samples to evaluate similarity scores and train machine learning (Boult: fig 2-3, Abstract) thereby improves cluster[ing] of large number of image objects as small groups and/or partitioned object images, while maintaining the relationship between image object similarities (Liu: 0016), thus improves overall quality and reliability of the system. As to claim 45, the combination of Boult, Mitura, Liu disclosed assigning each of the plurality of probe images to an individual vertex in a graph (Boult: fig 2-3); “assigning each of the plurality of gallery images to an individual vertex in the graph”( Boult: fig 6, 0061-0062) ; and “determining a similarity score for each pair of vertices in the graph” (Boult: 0045-0047, 0051,0054). As to claim 46, the combination of Boult, Mitura, Liu disclosed “wherein determining a graph Laplacian comprises: determining the graph Laplacian as L = D – W” ((Liu: 0006)) As to claim 47, the combination of Boult, Mitura, Liu disclosed “wherein determining a graph Laplacian comprises: determining the graph Laplacian as L = / - D-1W” (Liu: 0017-0018) As to claim 48, the combination of Boult, Mitura, Liu disclosed “wherein determining a graph Laplacian comprises: determining the graph Laplacian as L = /-D-1/2WD-1/2”” ((Liu: 0018-0019) As to claim 49, the combination of Boult, Mitura, Liu disclosed “comparing the eigenvalues or function thereof against a threshold” (Liu: 0028,0031). PNG media_image9.png 720 461 media_image9.png Greyscale As to claim 50, the combination of Boult, Mitura, Liu disclosed “ wherein the threshold is a negative number” (Liu: 0020,0028) As to claim 51, the combination of Boult, Mitura, Liu disclosed “determining a similarity score between one of the plurality of probe images and one of the plurality of gallery images” (Boult: fig 2-3, 0045-0047, 0051,0054). As to claim 52, the combination of Boult, Mitura, Liu disclosed “determining a similarity score between each pair of images in a set of images comprised of the plurality of probe images and the plurality of gallery images” (Boult: fig 2-3, 0045-0047, 0051,0054, 0061-0062). PNG media_image10.png 97 223 media_image10.png Greyscale As to claim 58, the combination of Boult, Mitura, Liu disclosed wherein the combination is done in the eigenspace for each biometric or related component (Liu: 0028,0031). Conclusion The prior art made of record a. US Pub. No. 2011/0106734 b. US Pub. No. 2013/0148898 c. US Pub. No 2008/0275862 Examiner's Note: Examiner has cited particular columns and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner. SEE MPEP 2141.02 [R-5] VI. PRIOR ART MUST BE CONSIDERED IN ITS ENTIRETY, INCLUDING DISCLOSURES THAT TEACH AWAY FROM THE CLAIMS: A prior art reference must be considered in its entirety, i.e., as a whole, including portions that would lead away from the claimed invention. W.L. Gore & Associates, Inc. v. Garlock, Inc., 721 F.2d 1540, 220 USPQ 303 (Fed. Cir. 1983), cert. denied, 469 U.S. 851 (1984) In re Fulton, 391 F.3d 1195, 1201,73 USPQ2d 1141, 1146 (Fed. Cir. 2004). >See also MPEP §2123. In the case of amending the Claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention. The prior art made of record, listed on form PTO-892, and not relied upon, if any, is considered pertinent to applicant's disclosure Authorization for Internet Communications The examiner encourages Applicant to submit an authorization to communicate with the examiner via the Internet by making the following statement (from MPEP 502.03): “Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with the undersigned and practitioners in accordance with 37 CFR 1.33 and 37 CFR 1.34 concerning any subject matter of this application by video conferencing, instant messaging, or electronic mail. I understand that a copy of these communications will be made of record in the application file.” Please note that the above statement can only be submitted via Central Fax (not Examiner's Fax), Regular postal mail, or EFS Web using PTO/SB/439. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Srirama Channavajjala whose telephone number is 571-272-4108. The examiner can normally be reached on Monday-Friday from 8:00 AM to 5:30 PM Eastern Time. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Gorney, Boris, can be reached on (571) 270- 5626. The fax phone numbers for the organization where the application or proceeding is assigned is 571-273-8300 Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free) /Srirama Channavajjala/Primary Examiner, Art Unit 2154
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Prosecution Timeline

Mar 14, 2024
Application Filed
May 17, 2025
Non-Final Rejection — §101, §103, §DP
Aug 17, 2025
Response Filed
Sep 06, 2025
Final Rejection — §101, §103, §DP
Mar 03, 2026
Examiner Interview Summary
Mar 03, 2026
Applicant Interview (Telephonic)
Mar 10, 2026
Request for Continued Examination
Mar 17, 2026
Response after Non-Final Action
Mar 27, 2026
Non-Final Rejection — §101, §103, §DP (current)

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