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 .
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 12/31/25 has been entered.
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 1 and 3-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1 and 3-21 are directed to an abstract idea without significantly more. The claims recite a mental process that can be performed by a human being and/or mathematical concepts and/or training/employing a machine learning model in a particular technological environment.
In regard to Claims 1 and 11, the following limitations can be performed as a mental process by a human being in terms of claiming collecting data, analyzing that data, and providing outputs based on that analysis which has been held by the CAFC to be an abstract idea in decisions such as, e.g., Electric Power Group, University of Florida Research Foundation, and Yousician v Ubisoft (non-precedential); and/or claim mathematical concepts as outlined at MPEP 2106.04(a)(2)(I); in terms of the Applicant claiming:
[a] […] method for […] scoring a dartboard using a single […] image, comprising:
[receiving] the […] image of the dartboard from a single perspective;
[…] acquiring in the […] image at least four predefined dartboard calibration points in an image plane;
[…] computing a homography transformation matrix that transforms any point in the image plane to a corresponding point in a dartboard plane;
[…] detecting a dart landing position in the image plane using [an algorithm] configured to detect keypoints, and transforming the dart landing position in the image plane to a dart landing position in the dartboard plane;
computing a score of the detected dart based on the dart landing position in the dartboard plane relative to the dartboard calibration points in the dartboard plane using a geometrical scoring function; and
displaying the score […].
In regard to Claims 1 and 11, Applicant claims training/employing a machine learning algorithm in a particular environment which has held by the CAFC to be abstract in, e.g., Recentive Analytics v. Fox Corp (2023-2437; 4/18/25), in terms of the Applicant claiming using a trained neural network to detect keypoints.
In regard to the dependent claims, they also claim an abstract idea to the extent that they merely claim further limitations that likewise could be performed as a mental process by a human being, and/or mathematical concepts and/or training/employing a machine learning model in a particular technological environment.
Furthermore, this judicial exception is not integrated into a practical application because to the extent that additional elements are claimed either alone or in combination such as, e.g., embodying Applicant’s abstract idea as computer instructions being executed by a processor, dartboards and darts, a digital image capture device having a sensor for capturing a digital image, and/or a computing device comprising a mobile device, these are merely claimed to add insignificant extra-solution activity to the judicial exception (e.g., data gathering), to embody the abstract idea on a general purpose computer, and/or do no more than generally link the use of a judicial exception to a particular technological environment or field of use. In this regard, see MPEP 2106.04(d)(I) in regard to “courts have also identified limitations that did not integrate a judicial exception into a practical application…”
Furthermore, the claims do not include additional elements that taken individually, and also taken as an ordered combination, are sufficient to amount to significantly more than the judicial exception because to the extent that, e.g., embodying Applicant’s abstract idea as computer instructions being executed by a processor, dartboards and darts, a digital image capture device having a sensor for capturing a digital image, and/or a computing device comprising a mobile device, these are well-understood, routine, and conventional elements and are claimed for the well-understood, routine, and conventional functions of collecting and processing data and/or providing an analysis/outputs based on that processing. To the extent that an apparatus is claimed as an additional element said apparatus fails to qualify as a “particular machine” to the extent that it is claimed generally, merely implements the steps of Applicant’s claimed method, and is claimed merely for purposes of extra-solution activity or field of use. See MPEP 2106.05(b). As evidence that these additional elements are well-understood, routine, and conventional, Applicant’s specification discloses the support for these elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a). See, e.g., F1-2 and 8 in Applicant’s PGPUB and text regarding same.
Response to Arguments
Applicant argues in its Remarks in regard to the rejections made under 35 USC 101:
PNG
media_image1.png
365
663
media_image1.png
Greyscale
Applicant’s arguments are not persuasive. Applicant’s claimed limitations in regard to employing a “trained neural network” are not identified in the 101 rejection made supra as being part of the alleged mental process, but are instead separately identified as being their own abstract idea, citing Recentive Analytics. Applicant’s claimed limitations in regard to employing a “homography transformation matrix” are identified as being abstract as a mental process and/or a mathematical concept. Applicant’s own PGPUB identifies the claimed transformation matrix as being a mathematical function (see, e.g., paragraph 70), which is consistent with other authorities (“Homography is a transformation matrix that defines a projective transformation between two images”; https://www.geeksforgeeks.org/computer-vision/what-is-homography-how-to-estimate-homography-between-two-images/). And to the extent that Applicant claims a mathematical process it necessarily is something that also could be performed mentally. Applicant’s subsequent argument in regard to employing a “direct linear transformation algorithm” is also unpersuasive and for similar reasons. Applicant’s PGPUB provides no detail in regard to what it means to employ such an algorithm (see, e.g., p70). And other authorities indicate that such an algorithm involves solving a series of math equations (see https://en.wikipedia.org/wiki/Direct_linear_transformation). What is more, if these are, in fact, functions that necessarily require a computer to perform (and, thereby, not part of the alleged abstract idea) then they would not be enabled based on the limited disclosure in regard how to make and/or use them in Applicant’s PGPUB and, therefore, would not constitute “significantly more” than Applicant’s abstract idea as they must be well-known, routine, and conventional.
Applicant further argues that its claimed subject matter is analogous to that of the Office’s 101 Example 47. It is unclear, however, how to apply the Examples provided by the Office given that the Mayo test is a legal test and the Office as part of the executive branch cannot make law; the Examples do not themselves cite to relevant legal authority; and because the Examples are not provided with a specification that would allow the BRI of the limitations in question to be determined. What is more, some of the Examples appear to be inapposite to precedential legal authority. To the extent that Applicant claims, for example, employing a “trained neural network to detect keypoints” such use of a machine learning model in a particular technological environment has been identified by the CAFC to be an abstract idea itself in decisions such as, e.g., Recentive Analytics. In other words, Applicant merely employs its claimed machine learning model to provide an output based on an input, which is what every machine learning model is employed for and is not, therefore, any improvement to machine learning model technology. What is more, Applicant’s disclosure in regard to how to employ the “trained neural network” is so limited that it could not possibly be enabling were this technology not already well-known, routine, and conventional. Applicant’s PGPUB provides this sole disclosure in regard to how to train the neural network:
PNG
media_image2.png
151
316
media_image2.png
Greyscale
Applicant’s disclosure basically says here to “train the neural network so that the neural network is trained to be really accurate.” Such a limited disclosure would not be enabling were this technique already well-known, routine, and conventional and, therefore, even if employing the neural network was not considered itself an abstract idea the addition of the neural network to Applicant’s claimed invention would not constitute “significantly more” than that abstract idea.
Applicant’s argument in regard to its new Claim 21 are not persuasive and for the reasons already stated supra.
Conclusion
The prior art made of record and not relied upon is listed in the attached PTO-Form 892 and is considered pertinent to applicant's disclosure.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Mike Grant whose telephone number is 571-270-1545. The Examiner can normally be reached on Monday through Friday between 8:00 a.m. and 5:00 p.m., except on the first Friday of each bi-week.
If attempts to reach the Examiner by telephone are unsuccessful, the Examiner's Supervisory Primary Examiner, Peter Vasat can be reached at 571-270-7625. 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 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.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MICHAEL C GRANT/Primary Examiner, Art Unit 3715