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 .
RCE Acknowledgement
Applicant’s Request for Continued Examination (RCE) dated 01/06/2026 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office Action has been withdrawn pursuant to 37 CFR 1.114, and the Applicant's RCE submission filed on 06 JANUARY 2026 has been entered.
Status of Claims
Claims 1-13 are pending in this instant application per RCE claim amendments and remarks filed on 01/06/2026 by Applicant. Claims 1, 12 and 13 are three/3 independent claims reciting non-transitory computer-readable storage medium, method and device claims. Claims 2-11 are claims dependent on Claim 1. Said 01/06 RCE amendments have amended Claims 1-2, 4, 8-9 and 12-13.
Amended Title filed on 01/06/2026 by the Applicant has been considered and entered.
Examiner notes that the Applicant has neither provided an English translation of its JP foreign application to confirm its priority date nor addressed it in RCE Remarks of 01/06/2026, and Foreign Priority Date has been maintained below. Attached Interview Summary documents the phone call made by Examiner in this regard.
This Office Action is a non-final rejection in response to RCE claim amendments and remarks filed by the Applicant on 06 JANUARY 2026 for its original application of 07 DECEMBER 2023 that is titled: “Information Processing Program, Information Processing Method, and Information Processing Device”.
Accordingly, amended Claims 1-13 are now being rejected herein.
Foreign Priority Date
Examiner acknowledges the receipt of Applicant’s foreign language application in Japanese (see copy attached as Appendix in previous Office Action mailed out on 10/02/2025), and notes that the Applicant is required to provide a certified English translation of its foreign language application for completion of its foreign priority, and to antedate a reference that could be used in rejection of claimed limitations. If the certified English translation was already provided, the Applicant is requested to furnish the details of such submission in its response to this Office Action. Thus, the final foreign priority date decision is deferred until an Allowance Office Action is mailed out and that no reference is traversed by the Applicant based on its foreign priority date.
Please see attached Interview Summary wherein Atty. Scott Elchert had agreed on March 2, 2026 to provide said English language translation.
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.
(NOTE: Latest ‘amendments to the claims’ filed by the Applicant in the RCE on 01/06/2026 are shown as bold and underlined additions, and all deletions may not be shown, or may not be underlined when stricken through. Underlined amendments to the claims that are shown below are from previously submitted claim amendments by the Applicant.)
Claims 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more, wherein Claims 1, 12 and 13 are independent non-transitory computer-readable medium, method and device claims respectively.
Exemplary Analysis.
Claim 1: Ineligible.
The claim recites a series of steps. The claim is directed to a non-transitory computer-readable medium reciting a series of steps to execute a process (method), which is a statutory category of invention (Step 1 -- YES).
The claim is analyzed to determine whether it is directed to a judicial exception. The claim recites the limitations of: generating [[]] and storing time-series data structure mapping frame timings to coordinate positions of the tracked [[]] product region; receiving a scan timing signal indicating a timing when first information regarding a first product registered by the user; specifying certain image data of the product held by the hand of the user from a frame corresponding to the identified target set of coordinate positions; specifying second information regarding the product included in the certain image data; and generating an alert when the first information and the second information do not match. In other words, the claim describes: extracting image data that include products; specifying first information regarding first product, and specifying second information regarding second product; and generating an alert when the first information and the second information do not match (see Abstract). These limitations, as drafted, are steps of a method that, under its broadest reasonable interpretation, covers performance of the limitations via a method of organizing human activity such as fundamental economic principles or practices (based on products for purchase/ sale and self-checkout machine 50, that includes hedging, insurance, mitigating risk), and/or commercial or legal interactions (based on registration machine and fraud detection unit 116, that includes agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations), and/or managing behavior or relationships or interactions between people (based on alert and alarm notification and warning control unit 117, that includes social activities, teaching, and following rules or instructions), but for the recitation of generic computer/s and/or computer component/s such as the devices/ mobile devices. These limitations fall under the “certain methods of organizing human activity” group (Step 2A1 -- YES).
Next, the claim is analyzed to determine if it is integrated into a practical application. The claim recites additional elements of registration machine, extracting and relationship devices, and a machine learning model in completing steps: acquiring video data each video [[]] data [[]] including image data of a registration machine used to register a product by a user; and continuously tracking, by repeatedly applying a first machine learning model to a plurality of image data frames from the acquired video data, [[]] a product region that includes a product held by a hand of the user, [[]] a second region that includes the product, and a holding relationship between the first region and the second region[[]]. These additional elements are considered extra-solution activities. The registration machine, the extracting and relationship devices, and the machine learning model in these steps are recited at a high level of generality, i.e., as generic processors performing generic computer/s functions of processing data. These generic processors are no more than mere instructions to apply the exception using generic computer/s and/or computer component/s. Accordingly, these additional elements do not integrate the abstract idea into a practical application, because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claim is directed to the abstract idea (Step 2A2 -- NO).
Next, the claim is analyzed to determine if there are additional elements in this claim that individually, or as an ordered combination, ensure that the claim amounts to significantly more than the abstract ideas (whether claim provides inventive concept). As discussed with respect to Step 2A2 above, the additional elements in the claim amount to no more than mere instructions to apply the exception using generic computer/s and/or computer component/s. The same analysis applies here in Step 2B, i.e., mere instructions to apply an exception using a generic computer and/or computer components over a network cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. Because the additional elements described above were considered to be extra-solution activities in Step 2A, they are re-evaluated in Step 2B to determine if they are more than what is well-understood, routine and conventional in the field. The disclosure does not provide any indication that these devices (processors) are anything other than generic processors and the Symantec, TLI, and OIP Techs. court decisions (MPEP 2106.05 (d) (II)) indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Also, paras [0052]-[0055] and [0059]-[0060] and [0066] of the Applicant’s own Specification (US Pub. No. 2024/ 0211952 published on 27 JUNE 2024) describe the two machine learning models as ---
{“[0052] FIG. 3 is a functional block diagram illustrating a functional configuration of the information processing device 100 according to the first embodiment. As illustrated in FIG. 3, the information processing device 100 includes a communication unit 101, a storage unit 102, and a control unit 110. ……………………………………………………………..
[0053] The communication unit 101 is a processing unit that controls communication with another device and, for example, is implemented by a communication interface or the like. For example, the communication unit 101 receives video data from the camera 30 and transmits a processing result by the control unit 110 to the administrator’s terminal 60. …………………………………………………………………………………………………..
[0054] The storage unit 102 is a processing unit that stores various types of data, programs executed by the control unit 110, or the like, and is implemented by a memory, a hard disk, or the like. The storage unit 102 stores a training data database (DB) 103, a first machine learning model 104, a second machine learning model 105, a video data DB 106, and a coordinate position DB 107. …...........................................
[0055] The training data DB 103 is a database that stores training data used to train the first machine learning model 104 and training data used to train the second machine learning model 105. For example, an example will be described where Human-Object Interaction Detection (HOID) is adopted for the first machine learning model 104, with reference to FIG. 4. FIG. 4 is a diagram for explaining training data. As illustrated in FIG. 4, each piece of the training data includes image data to be input data and correct answer information (label) set to the image data. ……………………………………………………
[0059] Returning to FIG. 3, the first machine learning model 104 is an example of a machine learning model that is trained to identify a person and an object imaged in training data (for example, person and storage (plastic bag or the like)). Specifically, the first machine learning model 104 is a machine learning model that identifies the person, the product, and the relationship between the person and the product from the input image data, and outputs an identification result. For example, the first machine learning model 104 can adopt the HOID and can also adopt a machine learning model using various neural networks or the like. In a case of the HOID, “the class and the region information of the person, the class and the region information of the product (object), and the interaction between the person and the product” are output. ………………………..
[0060] The second machine learning model 105 is an example of a machine learning model trained to specify an item of a product imaged in training data. For example, the second machine learning model 105 may be implemented by a zero-shot image classifier. In this case, the second machine learning model 105 uses a list of texts and an image as inputs and outputs a text having the highest similarity to the image, in the list of the texts, as a label of the image. ……………………………………………………………………………
[0066] The machine learning unit 111 is a processing unit that performs machine learning of the first machine learning model 104 and the second machine learning model 105, using each piece of the training data stored in the training data DB 103. Note that the first machine learning model 104 and the second machine learning model 105 may be machine learned in advance, and the machine learning unit 111 can execute the following processing as fine tuning in a case where accuracy of the machine-learned first machine learning model 104 and second machine learning model 105 is insufficient.”} ---
and indicate that the concept described by the extra-solution additional element is conventional. Accordingly, a conclusion that the aforementioned extra-solution additional elements are well-understood, routine and conventional activity is supported under Berkheimer options 2 and 3, respectively.
Viewing the limitations as an ordered combination does not add anything further than looking at the limitations individually. When viewed either individually, or as an ordered combination, the additional elements do not amount to a claim as a whole that is significantly more than the abstract idea itself. Therefore, the claim does not amount to significantly more than the recited abstract idea (Step 2B -- NO), and the claim is not patent eligible.
The analysis above applies to all statutory categories of the invention including independent method Claim 12 and independent device Claim 13, which perform the steps similar to those of the independent non-statutory computer-readable storage medium Claim 1. Furthermore, the limitations of dependent non-statutory computer-readable storage medium Claims 2-11, further narrow the independent non-statutory computer-readable storage medium Claim 1 with additional steps and limitations (e.g., inputting the acquired video data to a machine learning model ……; extracting the image data ……; specifying the certain image data ……; notifying a terminal of a clerk of identification information ……; generating an alert regarding an abnormality in a behavior ……; causing a camera included in the registration machine to image the user ……; …… notifying of an alert regarding an abnormality of the product registered in the registration machine; specifying a timing with reference to an operation of registering the item of the product with no barcode into the registration machine ……; scanning a barcode of a product with the barcode ……; specifying a timing with reference to an operation of registering the item of the product ……; etc. ), and do not resolve the issues raised in rejection of the independent non-statutory computer-readable storage medium Claim 1.
Therefore, said Claims 1-13 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Response to Arguments
Applicant's RCE remarks (on pages 10-14) and claim amendments dated 06 JANUARY 2026 with respect to the rejection of amended Claims 1-13 have been carefully considered, but they are not persuasive and do not put these amended claims in a condition ready for Allowance. Thus, the rejection of amended Claims 1-13 has been maintained under 35 USC 101 as described above. Additionally, Examiner notes that all of the previous Claim Objections have now been withdrawn based on RCE claim amendments, and amended Title has been considered and entered. Thus, the rejection of amended Claims 1-13, as described above, is being maintained herein under 35 USC 101 with some modifications in this Office Action, where needed to provide clarification in response to the Applicant’s claim amendments and remarks of 01/06/2026.
In response to the Applicant’s RCE arguments of 01/06/2026 traversing 101 rejection and arguing “I. The Amended Claims Recite a Specific Technological Improvement, Not an Abstract Idea” (on pages 10-11) and stating on top of page 11 --- {“It is a specific technical solution to the problem of how to efficiently and accurately correlate two disparate data streams: a continuous, high-volume video stream and a discrete, asynchronous event signal from a POS system.”}. Examiner respectfully disagrees for at least the following reasons --- (a) there is no claim language claiming phrases of “high-volume video stream” nor “discrete, asynchronous event”; (b) there is no support in the Specification for phrases of “high-volume video stream” nor “discrete, asynchronous event”; (c) at least US Pub. No. 2014/ 0289323 filed by Kutaragi et al. that antedates the instant application and teaches in para [0037] about “live stream video distribution”, “stream videos”, “live video distribution”, “live-streaming video distribution that continues on and on”, etc.; and (d) at least the attached paper “On the History of Discrete Event Systems” from Science Direct, Volume 45, 2018, pages 213-222 (attached herewith as Appendix) shows that Discrete Event Systems were well-known and antedate the instant application.
In response to the Applicant’s RCE arguments of 01/06/2026 traversing 101 rejection and arguing “II. The Amended Claims Provide an Inventive Concept by Unconventionally Integrating System Components” (on pages 12-13) and stating as follows --- {“The claimed invention defines a unique event-driven data retrieval architecture for video analysis, wherein: …………. it acts as a real-time trigger for a database query.,”}. Examiner respectfully disagrees for at least the following reasons --- (a) there is no claim language claiming phrases of “event-driven data retrieval”/”event-driven”/”data retrieval” nor “real-time trigger”/”trigger” nor “database query”; (b) there is no support in the Specification for phrases of “event-driven data retrieval”/“event-driven”/”data retrieval” nor “real-time trigger”/”trigger” nor “database query”; (c) at least US Pub. No. 2014/ 0289323 filed by Kutaragi et al. that antedates the instant application and teaches in para [0157] about “successively retrieves detailed data and design data”, while paras [0198]-[0199] teach about “data are retrieved”, etc.; and (d) at least US Pub. No. 2011/ 0066658 filed by Rhoads et al. that antedates the instant application and teaches in paras [0243] & [0290] for “query a database”, and para [0441] for “query the database”, and para [0488] for “query the database 17”.
Furthermore, Examiner has provisionally withdrawn 103 rejection as Ishida reference or Ushiwida reference can be added as a fifth reference for obviousness rejection subject to the Applicant’s response in confirmation of its foreign priority date. Irrespectively, Examiner notes specifically two references, viz., Ishida et al.’s reference per Pub. No. US 2024/ 0193995 filed on 08/23/2023 with a foreign (JP) priority date of 12/07/2022 that teaches about at least --- HOID, 1st/2nd/3rd learning machine models, extracts a region of the commodity product, and time series; AND Ushijima et al.’s reference per Pub. No. US 2023/ 0100920 filed on 06/30/2022 with a foreign (JP) priority date of 09/30/2021 that teaches about at least --- HOID, time series, product region coordinates, and extracted entries.
In response to the Applicant’s arguments of 08/21/2025 against the rejection under 35 USC 101, Examiner respectfully disagrees. Also, Examiner clarifies that the instant application is nothing more than an improvement of an abstract idea, wherein using technology/ computers to execute an abstract idea is at most an improvement to the abstract idea. Furthermore, Examiner notes that latest claim amendments of 08/21 fall under both --- abstract idea and extra-solution activities --- as described above in the 101 rejection in paras 8. and 9./10. respectively.
In further response to the 08/21/2025 arguments traversing the 35 USC 101 rejection, Examiner disagrees with Applicant’s arguments about the instant application --- {“Specifically, amended Claim 1 recites a specific, unconventional technical architecture comprising two different machine learning models with distinct, sequential roles.”}. Examiner notes that two models described in the instant application’s Specification --- Bbox and HOI (Human-Object Interaction) detection models --- have been well-known about a decade prior to date for filing the instant application, and how these two models have progressed in this industry. Furthermore, attached as Appendix (of google search) that describes: the Bbox (Bounding box) detection model debuted in 2001 with further improvements as R-CNN in 2014 and YOLO in 2015; while the HOI detection models debuted in mid-2000s to early 2010s with further improvements by release of HICO (Humans Interacting with Common Objects) dataset in 2015 and HICO-DET in 2018, and first end-to-end HOI model developed in 2021 (see deep dive print out Appendix) --- all of which happened, per google search in Appendix, before the priority date of the instant application of 12/23/2022.
Conclusion
The prior art made of record and not relied upon, listed in Form 892, that is considered pertinent to the Applicant's disclosure and review for not traversing already issued patents and/or claimed inventions by the claims of the current invention of the Applicant. Examiner notes that Form 892 contains more references than those cited in the rejection above under 35 USC 103, and that all the references cited on said Form 892 are relevant to this application and form a part of the body of prior art.
The Examiner has pointed out particular references contained in the prior art of record in the body of this action for the convenience of the Applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. The Applicant should consider the entire prior art as applicable as to the limitations of the claims; and said prior art includes references with synonyms for terms used in the claims that have been interpreted under the BRI (broad reasonable interpretation) procedures of the Office. It is respectfully requested from the Applicant, in preparing the response, to consider fully the entire references 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.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Sanjeev Malhotra whose telephone number is (571) 272-7292. The Examiner can normally be reached during Monday-Friday between 8:30-17:00 hours on a Flexible schedule.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, the Applicant is encouraged to contact the Examiner directly.
If attempts to reach the Examiner by telephone are unsuccessful, the examiner’s supervisor, Abhishek Vyas, can be reached on (571) 270-1836. The facsimile/fax phone number for the organization, where this application or proceeding is assigned, is 571-273-8300.
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Electronic Communications
Prior to initiating the first e-mail correspondence with an Examiner, Applicant is responsible for filing a written statement with the USPTO in accordance with MPEP §502.03(II). All received e-mail messages including e-mail attachments shall be placed into this application’s record. The Examiner’s e-mail address is provided below at the end of this Office Action.
/S.M./
Examiner, Art Unit 3691
sanjeev.malhotra@uspto.gov
/ABHISHEK VYAS/Supervisory Patent Examiner, Art Unit 3691
Prosecution Insights