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 .
Priority
Receipt is acknowledged of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Information Disclosure Statement
The information disclosure statements (IDSs) submitted on 3 July 2024 and 9 May 2025 complies with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
35 USC § 101 Statutory Analysis
The claims do not recite any of the judicial exceptions enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance. Further, the claims do not recite any method of organizing human activity, such as a fundamental economic concept or managing interactions between people. Finally, the claims do not recite a mathematical relationship, formula, or calculation. Thus, the claims are eligible because they do not recite a judicial exception.
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 23-24 are rejected under 35 U.S.C. §101 because the claimed invention is directed to non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because the broadest reasonable interpretation of the claimed “Learning data consisting of a pair of a pseudo image and pseudo object region data”, consistent with a conclusion reached by one skilled in the art based on both the specification disclosure and the state-of-the-art, is that the full scope covers transitory “signal” embodiments.
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 23-24 are rejected under 35 U.S.C. §101 because the claimed invention is directed to an abstract idea without significantly more.
The following analysis is based on the 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG) published on January 7, 2019 (84 Fed. Reg. 50). See Also MEPE 2106.04(a)(2)(II).
With regard to claims 23-24:
Step 1:
Claims 23-24 do not meet step 1 requirement as they are not directed towards a process, machine, manufacture or composition of matter which is/are statutory subject matter. In this case, “learning data consisting of a pair of a pseudo image and pseudo object region data” does not satisfy any of the statutory subject matter categories.
Step 2A, prong 1 test:
Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes, claim 1 as a whole recites a method facilitating steps of organizing human activity e.g., mental process as explained in details below.
Claims 23 and 24 in general is provides for “learning data consisting of a pair of a pseudo image and pseudo object region data, wherein the pseudo object region data is data indicating any pseudo object region, the pseudo image is an image obtained by combining a pseudo residual image and an original image, and the pseudo residual image is an image showing a change in a pixel value given to the original image by a presence of a pseudo object in the pseudo object region” and “wherein the pseudo object region data includes a plurality of pieces of the pseudo object region data in which at least one of a position, a size, or a shape of the pseudo object region is different, receiving a frame of a video stream, generating input channel values corresponding to the frame, receiving an output state vector comprising frame-wide statistics calculated based on input channel values corresponding to a previous frame of the video stream, processing the frame of the video stream based on the output state vector”.
The limitations of “learning data consisting of a pair of a pseudo image and pseudo object region data, wherein the pseudo object region data is data indicating any pseudo object region, the pseudo image is an image obtained by combining a pseudo residual image and an original image, and the pseudo residual image is an image showing a change in a pixel value given to the original image by a presence of a pseudo object in the pseudo object region” and “wherein the pseudo object region data includes a plurality of pieces of the pseudo object region data in which at least one of a position, a size, or a shape of the pseudo object region is different, receiving a frame of a video stream, generating input channel values corresponding to the frame, receiving an output state vector comprising frame-wide statistics calculated based on input channel values corresponding to a previous frame of the video stream, processing the frame of the video stream based on the output state vector” as drafted, is data, under its broadest reasonable interpretation, covers performance of the limitation in a mental process/step (a mathematical relationship, formula, or calculation). That is, nothing in the claim element precludes the processing from being performed as a mental process, or merely on pencil and paper.
If a claim limitation, under its broadest reasonable interpretation, covers performance of a mental step which could be performed with pen and paper, then it falls within the “mental steps” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A, prong 2 test:
Does the claim recite additional elements that integrate the judicial exception into a practical application? No as explained below.
The claim does not recite any physical elements nor does it recite additional elements that integrate the judicial exception into a practical application. As will be explained below, these various elements can be performed as mental steps. With respect to the functions of “learning data consisting of a pair of a pseudo image and pseudo object region data, wherein the pseudo object region data is data indicating any pseudo object region, the pseudo image is an image obtained by combining a pseudo residual image and an original image, and the pseudo residual image is an image showing a change in a pixel value given to the original image by a presence of a pseudo object in the pseudo object region” and “wherein the pseudo object region data includes a plurality of pieces of the pseudo object region data in which at least one of a position, a size, or a shape of the pseudo object region is different, receiving a frame of a video stream, generating input channel values corresponding to the frame, receiving an output state vector comprising frame-wide statistics calculated based on input channel values corresponding to a previous frame of the video stream, processing the frame of the video stream based on the output state vector” the broadest reasonable interpretation would have encompassed any forms of calculating inclusive of mental calculations.
Step 2B:
Does the claim recite additional elements that amount to significantly more than the judicial exception? No as explained below.
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 recites an abstract idea.
This judicial exception does not amount to significantly more because it 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. In particular, the claims do not recite additional elements to integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The claims are not patent eligible.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. §102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claims 23 and 24 are rejected under 35 U.S.C. §102(a)(1) as being anticipated by Watanabe (JP2019046269A) (hereafter referred to as “Watanabe”).
With regard to claim 23, Watanabe describes learning data consisting of a pair of a pseudo image and pseudo object region data, wherein the pseudo object region data is data indicating any pseudo object region, the pseudo image is an image obtained by combining a pseudo residual image and an original image, and the pseudo residual image is an image showing a change in a pixel value given to the original image by a presence of a pseudo object in the pseudo object region (refer for example to page 10, lines 8-28, which describes a system that generates a plurality of pseudo-label images, the "data indicating an arbitrary pseudo-object area" and generates a pseudo-sample image (corresponding to the "pseudo-image" from each of the pseudo-label images, and refer to page 6, lines 5-9 which discusses “showing a change in a pixel value”).
As to claim 24, Watanabe describes wherein the pseudo object region data includes a plurality of pieces of the pseudo object region data in which at least one of a position, a size, or a shape of the pseudo object region is different (refer to page 10, lines 8-28, which describes the "plurality of pseudo-object area data in which at least one of the position, the size, and the shape of the pseudo-object area is different", and refer to page 6, lines 5-9 which discusses “showing a change in a pixel value”).
Claims 1, 10, 11, 15, 16, 18 and 20-24 are rejected under 35 U.S.C. §102(a)(1) as being anticipated by Zhu et al. (CN-112733744-A) (hereafter referred to as “Zhu”).
With regard to claim 1, Zhu describes a first processor (refer for example to page 21, lines 1-6) wherein the first processor is configured to perform first reception processing of receiving an input of pseudo object region data indicating any pseudo object region (refer for example to page , lines ); and pseudo residual image generation processing of generating a pseudo residual image showing a change in a pixel value given to an original image by a presence of a pseudo object in the pseudo object region, based on the pseudo object region data (refer for example to page , lines ).
As to claim 10, describes wherein the first reception processing includes receiving an input of the original image (refer for example to page 21, lines 1-3), and the first processor (refer for example to page 21, lines 1-6) is configured to perform pscudo image generation processing of generating a pseudo image by combining the pseudo residual image and the original image (refer for example to page 9, line 28 through page 10, line 6, and to page 10, line 31 through page 11, line 17).
In regard to claim 11, Zhu describes wherein the pseudo image generation processing includes generating the pseudo image by addition or multiplication of the pseudo residual image and the original image (refer for example to page 9, line 28 through page 10, line 6, and to page 10, line 31 through page 11, line 17).
With regard to claim 15, Zhu describes wherein the first processor (refer for example to page 21, lines 1-6) is configured to generate learning data consisting of a pair of the pseudo image and the pseudo object region data (refer for example to page 9, line 28 through page 10, line 6, and to page 20, line 8 through line 29).
As to claim 16, describes wherein the first reception processing includes receiving an input of a plurality of pieces of the pseudo object region data in which at least one of a position, a size, or a shape of the pseudo object region is different (refer for example to page 13, line 27 through page 14, line 16), and the first processor (refer for example to page 21, lines 1-6) is configured to generate the learning data for each of the plurality of pieces of received pseudo object region data for the one original image (refer to page 9, line 28 through page 10, line 6, and to page 20, line 8 through line 29).
With regard to claim 18, Zhu describes a step of receiving, by the first processor (refer for example to page 21, lines 1-6), an input of pseudo object region data indicating any pseudo object region (refer for example to page 9, line 28 through page 10, line 6, and to page 20, line 8 through line 29); and a step of generating, by the first processor (refer for example to page 21, lines 1-6), a pseudo residual image showing a change in a pixel value given to an original image by a presence of a pseudo object in the pseudo object region, based on the pseudo object region data (refer for example to page 13, line 27 through page 14, line 16).
With regard to claim 20, Zhu describes a step of receiving, by the first processor (refer for example to page 21, lines 1-6), an input of the original image (refer for example to page 21, lines 1-3); and a step of generating, by the first processor (refer for example to page 21, lines 1-6), a pseudo image by combining the pseudo residual image and the original image (refer for example to page 9, line 28 through page 10, line 6, and to page 10, line 31 through page 11, line 17).
As to claim 21, describes a step of generating, by the first processor (refer for example to page 21, lines 1-6), learning data consisting of a pair of the pseudo image and the pseudo object region data (refer for example to page 9, line 28 through page 10, line 6, and to page 20, line 8 through line 29).
In regard to claim 22, Zhu describes a non-transitory, computer-readable tangible recording medium on which a program for causing, when read by a computer, a first processor provided to the computer to execute the image generation method according to claim 18 is recorded (refer for example to page 21, lines 1-6).
With regard to claim 23, Zhu describes learning data consisting of a pair of a pseudo image and pseudo object region data, wherein the pseudo object region data is data indicating any pseudo object region, the pseudo image is an image obtained by combining a pseudo residual image and an original image (refer for example to page 9, line 28 through page 10, line 6, and to page 20, line 8 through line 29), and the pseudo residual image is an image showing a change in a pixel value given to the original image by a presence of a pseudo object in the pseudo object region (refer for example to page 13, line 27 through page 14, line 16).
In regard to claim 24, Zhu describes wherein the pseudo object region data includes a plurality of pieces of the pseudo object region data in which at least one of a position, a size, or a shape of the pseudo object region is different (refer for example to page 13, line 27 through page 14, line 16).
Allowable Subject Matter
Claims 2-9, 12-14, 17 and 19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Relevant Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Liu, Jia (‘075) and (‘076), Shi and Li all disclose systems similar to applicant’s claimed invention.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jose L. Couso whose telephone number is (571) 272-7388. The examiner can normally be reached on Monday through Friday from 5:30am to 1:30pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella, can be reached on 571-272-7778. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
Information regarding the status of an application may be obtained from the Patent Center information webpage on the USPTO website. For more information about the Patent Center, see https://www.uspto.gov/patents/apply/patent-center. Should you have questions about access to the Patent Center, contact the Patent Electronic Business Center (EBC) at 571-272-4100 or via email at: ebc@uspto.gov .
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
/JOSE L COUSO/Primary Examiner, Art Unit 2667
January 23, 2026