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 .
Claim Rejections - 35 USC § 101
2. 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.
3. Claims 1-21 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
4. Step 1
Claims 1-21 are directed to an apparatus {system} meeting the requirements for Step 1.
5. Step 2A Prong 1
In independent Claim 1 (and similarly for Claims 8 and 17), recite a machine learning model which is a mathematical concept.
6. Step 2A Prong II
The abstract idea is not integrated into a practical application. According to MPEP 2106, a consideration indicative of integration into a practical application includes improvements to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)) or adding a specific limitation other than what is well-understood, routine, conventional activity, or adding unconventional steps that confine the claim to a particular application (a non-conventional and non-generic arrangement of various computer components for filtering Internet content, as discussed in BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1350-51, 119 USPQ2d 1236, 1243 (Fed. Cir. 2016) (MPEP § 2106.05(d)). Conversely, considerations not indicative of integration include adding words “apply it” (or equivalent) with the judicial exception or mere instructions to implement the abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. (MPEP 2106.05(f)); adding insignificant extra-solution activity (MPEP 2106.05(g)), or generally linking the use of the abstract idea to a particular technological environment or field of use (MPEP 2106.05(h)).
Here, a processor configured to implement a trained model are recited so generically (no details whatsoever are provided other than in name only) that they represent no more than mere instructions to apply the judicial exception on a computer. Applicant’s specification does not disclose that the processor with instructions is directed to a technological solution to a technological problem that “overcome some sort of technical difficulty.” (citing ChargePoint, Inc. v. SemaConnect, Inc., 920 F.3d 759, 768 (Fed. Cir. 2019).
According to Applicant’s specification:
Fig. 29 illustrates an exemplary computing system 300 that may be any of the mobile phones or capture devices 110, 160 used to train and implement embodiments of the present technology. The computing system 300 of Fig. 29 includes one or more processors 310 and main memory 320. Main memory 320 stores, in part, instructions and data for execution by processor unit 310. Main memory 320 can store the executable code when the computing system 300 is in operation. The computing system 300 of Fig. 29 may further include a mass storage device 330, portable storage medium drive(s) 340, output devices 350, user input devices 360, a display system 370, and other peripheral devices 380. [0178].
The Specification further discloses that the device can be used to address a national shortage of umpires ([0003, [0176]). Yet, this is a technological solution to a logistical or financial problem but not a technological problem.
Of note, in December 2025, the USPTO issued an advance notice that the MPEP will be updated to include Ex Pate Desjardins. The Ex Parte Desjardins decision analyzed eligibility in terms of whether the claims were directed to an improvement in the functioning of a computer, or an improvement to other technology or technical field under longstanding Federal Circuit precedent in Enfish, LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016) and McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299 (Fed. Cir. 2016). See also MPEP §§ 2106.04(d)(l) and 2106.05(a). The MPEP will contain in-part:
the claimed invention was a method of training a machine learning model on a series of tasks. The Appeals Review Panel (ARP) overall credited benefits including reduced storage, reduced system complexity and streamlining, and preservation of performance attributes associated with earlier tasks during subsequent computational tasks as technological improvements that were disclosed in the patent application specification…In Step 2A Prong Two, the ARP then determined that the specification identified improvements as to how the machine learning model itself operates, including training a machine learning model to learn new tasks while protecting knowledge about previous tasks to overcome the problem of “catastrophic forgetting” encountered in continual learning systems. Importantly, the ARP evaluated the claims as a whole in discerning at least the limitation “adjust the first values of the plurality of parameters to optimize performance of the machine learning model on the second machine learning task while protecting performance of the machine learning model on the first machine learning task” reflected the improvement disclosed in the specification. Accordingly, the claims as a whole integrated what would otherwise be a judicial exception instead into a practical application at Step 2A Prong Two, and therefore the claims were deemed to be outside any specific, enumerated judicial exception. (MPEP 2106.04 (d)(III).
According to Applicant’s specification no disclosure of improvements similar to those examples in Ex Parte Desjardins of reduced storage, reduced system complexity and streamlining, and preservation of performance attributes associated with earlier tasks during subsequent computational tasks as technological improvement (to overcome catastrophic forgetting) could be identified. (See Advance notice of change to the MPE in light of Ex Parte Desjardins, December 5, 2025).
Consequently, the processors are viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer or as a means to automate the steps. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2104(d)(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224, 110 USPQ2d 1976, 1983-84 (2014).
Even when the limitations are viewed in combination, the additional elements in this claim (i.e., processor, image camera, baseball instrumentalities) do no more than automate the steps needed to be performed, using the one of more computer components as tools. While this type of automation is an improvement in a general sense as opposed to performance manually, there is no change to the computers and other technology that are recited in the claim as automating the abstract ideas, and thus this claim cannot improve computer functionality or other technology. See, e.g., Trading Technologies Int’l v. IBG, Inc., 921 F.3d 1084, 1093 (Fed. Cir. 2019) (using a computer to provide a trader with more information to facilitate market trades improved the business process of market trading, but not the computer) and the cases discussed in MPEP 2106.05(a)(I), particularly FairWarning IP, LLC v. Latric Sys., 839 F.3d 1089, 1095 (Fed. Cir. 2016) (accelerating a process of analyzing audit log data is not an improvement when the increased speed comes solely from the capabilities of a general-purpose computer) and Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055 (Fed. Cir. 2017) (using a generic computer to automate a process of applying to finance a purchase is not an improvement to the computer’s functionality).
Accordingly, each claim, as a whole, does not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception. Thus, Claim 1, and similarly Claims 8 and 17, lack the eligibility requirements of Step 2 Prong II.
7. Step 2B
According to MPEP 2106, in addition to the considerations discussed in Step 2A, an additional consideration indicative of an inventive concept (aka “significantly more”) is the addition of a specific limitation other than what is well-understood, routine, conventional activity in the field (MPEP 2106.05(d)). Conversely, an additional consideration not indicative of an inventive concept is simply appending well-understood, conventional activities previously known to the industry, specified at a high level of generality, to the abstract idea (MPEP 2106.05(d) and Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018)). Thus, the additional elements evaluated under Step 2A are re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field.
Here, there is no extra-solution activity to revisit. Thus, Claims 1, 8 and 17 are ineligible.
8. Dependent Claims 2-7, 9-16, and 18-21
Claims 2-3, 9-10, and 19-21 recite additional instrumentalities used as data gathering tools to implement the abstract idea. Claims 4-7, 11-16, and 18 recite an extra-solution base-ball instrumentalities as part of the sporting environment and usage and data gathering conditions. Thus, none of the claims supply a practical application or inventive concept sufficient to transform the nature of the claim into a patent-eligible application.
Additionally, the combination of additional elements adds nothing that is not already present when considered individually where the additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which cannot provide an inventive concept. Thus, Claims 2-7, 9-16, and 18-21 are ineligible.
Claim Rejections - 35 USC § 102
9. 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
10. Claims 1, 4-9, 13-17 are rejected under 35 U.S.C. § 102 (a1)(a2) as being anticipated by U.S. Pat. Pub. No. 2023/0218971 to Hall.
In Reference to Claims 1 and 4
Hall discloses a system for determining a position of a moving object {baseball} relative to a reference object {strike zone} in a sporting event {baseball game} from image frames of the sporting event captured by an image capture device {cameras} (Abstr., Figs, 1, 4, and 5), comprising:
one or more processors configured to implement a machine learning model (“An embodiment of the tracking system. In one embodiment, the tracking system is composed of a plurality of cameras in functional communication with a machine-learning (ML) Engine programmed into a microcomputer.” [0095]) trained to identify the moving object and the reference object in one or more of the image frames (”The system may run continually, or may be set to detect that a pitcher has thrown the ball, and initiate a pitch trigger, flagging that a particular event happened in the software and readying the software to receive data about strike-zone and ball position and speed.” [0095], trained AI system [0109]); and
wherein the machine learning model is trained using a single image capture device (“primary camera” [0100, 0103]).
In Reference to Claim 5
Hall discloses constructing a strike zone over the home plate, and wherein the processor is further configured to size, position and orient the strike zone over home plate (“Strike-zone virtual imaging in real-time by mapping the strike zone in real time using coordinates on the batter and on the home plate” [0095, 0099, 0100, 0105, 0113]).
In Reference to Claim 6
Hall’s cameras identify a pitcher's mound (0116, 0117]), and orients the strike zone over home plate by directing the strike zone to face the pitcher's mound (strike zone is oriented over home plate so that a pitch passes through it [0047, 0048, 0095] where the position is oriented relative to the catcher’s position [0105] who is facing the pitcher’s mound).
In Reference to Claim 7
Hall discloses wherein the one or more processors are further configured to determine an image frame where the baseball or softball reaches a plane in which the strike zone is positioned, and to determine whether the baseball or softball passes through the strike zone at the image frame to constitute a strike, or whether the baseball or softball misses the strike zone at the image frame to constitute a ball ((“By analyzing the ball trajectory, we can determine whether the ball was hit or if it was missed by the batter. Also, based on the key points of the batter's pose, such as the knees, hip, ankle etc., and the relative position of the ball while it crosses the home plate, we can determine whether or not the pitch resulted in a valid hit, a strike or a ball.” ([0115], using primary camera [0100, 0103]).
In Reference to Claims 8 and 13
Hall discloses a system for determining a position of a moving object {baseball} relative to a reference object {strike zone} in a sporting event {baseball game} from image frames of the sporting event captured by an image capture device {cameras} (Abstr., Figs, 1, 4, and 5), comprising:
one or more processors configured to implement a machine learning model (“An embodiment of the tracking system. In one embodiment, the tracking system is composed of a plurality of cameras in functional communication with a machine-learning (ML) Engine programmed into a microcomputer.” [0095]) trained to identify the moving object and the reference object in one or more of the image frames (”The system may run continually, or may be set to detect that a pitcher has thrown the ball, and initiate a pitch trigger, flagging that a particular event happened in the software and readying the software to receive data about strike-zone and ball position and speed.” [0095], trained AI system [0109]); and
wherein the machine learning model is trained using only two-dimensional data (Hall discloses the use of the primary camera and secondary camera as input into the AI model ([0108] which provides two-dimensional data.)
In Reference to Claim 9
Hall discloses wherein the machine learning model is trained using ground truth data in which positions of at least one of the moving and reference objects are manually labeled ([0062]).
In Reference to Claim 14
Hall discloses constructing a strike zone over the home plate, and wherein the processor is further configured to size, position and orient the strike zone over home plate (“Strike-zone virtual imaging in real-time by mapping the strike zone in real time using coordinates on the batter and on the home plate” [0095, 0099, 0100, 0105, 0113]).
In Reference to Claim 15
Hall’s cameras identify a pitcher's mound (0116, 0117]), and orients the strike zone over home plate by directing the strike zone to face the pitcher's mound (strike zone is oriented over home plate so that a pitch passes through it [0047, 0048, 0095] where the position is oriented relative to the catcher’s position [0105] who is facing the pitcher’s mound).
In Reference to Claim 16
Hall discloses wherein the one or more processors are further configured to determine an image frame where the baseball or softball reaches a plane in which the strike zone is positioned, and to determine whether the baseball or softball passes through the strike zone at the image frame to constitute a strike, or whether the baseball or softball misses the strike zone at the image frame to constitute a ball ((“By analyzing the ball trajectory, we can determine whether the ball was hit or if it was missed by the batter. Also, based on the key points of the batter's pose, such as the knees, hip, ankle etc., and the relative position of the ball while it crosses the home plate, we can determine whether or not the pitch resulted in a valid hit, a strike or a ball.” ([0115], using primary camera [0100, 0103]).
In Reference to Claim 17
Hall discloses a system for determining a position of a baseball relative to a home plate in a baseball game from image frames of the baseball game captured by an image capture device (Abstr., Figs. 1, 4, and 5), comprising:
one or more processors configured to: implement a machine learning model trained to identify the home plate and the baseball in one or more of the image frames (“An embodiment of the tracking system. In one embodiment, the tracking system is composed of a plurality of cameras in functional communication with a machine-learning (ML) Engine programmed into a microcomputer.” [0095]),
construct a strike zone over the home plate size, position and orient the strike zone over home plate (“Strike-zone virtual imaging in real-time by mapping the strike zone in real time using coordinates on the batter and on the home plate” [0095, 0099, 0100, 0105, 0113]),
determine an image frame where the baseball or softball reaches a plane in which the strike zone is positioned and determine whether the baseball or softball passes through the strike zone at the image frame to constitute a strike, or whether the baseball misses the strike zone at the image frame to constitute a ball (“By analyzing the ball trajectory, we can determine whether the ball was hit or if it was missed by the batter. Also, based on the key points of the batter's pose, such as the knees, hip, ankle etc., and the relative position of the ball while it crosses the home plate, we can determine whether or not the pitch resulted in a valid hit, a strike or a ball.” ([0115], using primary camera [0100, 0103]).
In Reference to Claim 18
Hall discloses determine the image frame where the baseball reaches the plane in which the strike zone is positioned by measuring an increase in the number of pixels comprising the ball in the image frames. Specifically, “Ball location. Assuming the video frame is of height ‘H’ pixels and width ‘W’ pixels, the location of a ball implies the coordinates of the ball's center along the horizontal and vertical axes in terms of pixels in a given video frame.” [0023]. While Hall doesn’t express that there is an increase in pixels there necessarily must be an increase in pixels in the frame if there is a ball location in the frame defined by H x W pixels.
In Reference to Claim 19
Hall discloses wherein the machine learning model is trained using a single image capture (“primary” camera [0100, 0103]).
In Reference to Claim 20
Hall discloses wherein the machine learning model is trained using only two-dimensional data (Hall discloses the use of the primary camera and secondary camera as input into the AI model ([0108] which provides two-dimensional data.)
In Reference to Claim 21
Hall discloses wherein the machine learning model is trained on a single image capture device using only two-dimensional data (See rejection of Claims 1, 8, 19, and 20).
Claim Rejections - 35 USC § 103
11. 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.
12. 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.
13. The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
14. Claims 2-3 are rejected under 35 U.S.C. 103 as being unpatentable over Hall in view of U.S. Pat. Pub. No. 2022/0400202 to Imes.
Hall discloses the invention substantially as claimed. However, the reference does not explicitly disclose cameras comprising a smartphone, iPhone, or GoPro camera. One of skill in the art would be aware of the digital media processing of Imes.
Imes teaches of processing activity from one of more cameras (Abstr.) from an activity such as baseball activity [0043] where cameras gather data to train AI models ([0031, 0032, 0065, 0069]) include the use of various cameras. “According to an aspect, AI enabled camera 300 can include an HD camera, UHD camera, 4K camera, 8K camera, 360 degree camera, 3D camera, 4D camera, Augmented Reality (AR) Camera, security camera, mobile device such as a Samsung Galaxy s21 Ultra or an Apple iPhone 12 Pro, a drone having a camera such as DJI Spark Quadcopter, a GoPro camera capable of connecting to a mobile phone or other devices or various other digital image capturing devices capable of recording video.” [0063].
The Supreme Court in KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007) identified a number of rationales to support a conclusion of obviousness
(A) Combining prior art elements according to known methods to yield predictable results;
(B) Simple substitution of one known element for another to obtain predictable results;
(C) Use of known technique to improve similar devices (methods, or products) in the same way; and
(D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Here, it would require only routine skill in the art to modify the cameras of Hall with those of Imes in order to achieve the predictable result of increasing the robustness of the system by being interoperable with a broad range of familiar types and brands of camera devices. The Courts have held that simple substitution of one known element for another to obtain predictable results to be indicia of obviousness.
15. Claim 10-12 are rejected under 35 U.S.C. 103 as being unpatentable over Hall in view of U.S. Pat. Pub. No. 2011/0157227 to Ptucha.
In Reference to Claim 10
Hall discloses the invention substantially as claimed to include the annotation of elements of the baseball game in the camera images ([0062]). However, the reference does not explicitly disclose the annotating is performed manually. One of skill in the art would be aware of the camera and techniques for annotating of Ptucha.
Ptucha captures digital camera image data and analyzes the image data to generate extracted metadata tags and to append new or additional derived information to include labelling, captioning, and tagging applied automatically [0166].
It would have been obvious to one of ordinary skill in the art at the time the invention was made to automate the annotation of the camera images of Hall with the automation of Ptucha, since it has been held broadly providing a mechanical or automatic means to replace manual activity which has accomplished the same result involves only routine skill in the art. (In re Venner, 120 USPQ 192 (CCPA)).
In Reference to Claim 11
Hall discloses wherein the sporting event is a baseball game (Abstr.), the moving object is a baseball and the reference object is a home plate (“Strike-zone virtual imaging in real-time by mapping the strike zone in real time using coordinates on the batter and on the home plate” [0095, 0099, 0100, 0105, 0113]), and wherein the ground truth data ([0062]) for identifying home plate is automatically labeled (See Ptucha [0166]) using known positions of a pitcher’s mound relative to home plate. Hall discloses the baseball diamond [0116] which inherently or necessarily must disclose additional features such as first, second, third base and foul lines.
In Reference to Claim 12
Hall discloses wherein the sporting event is a baseball game (Abstr.), the moving object is a baseball and the reference object is a home plate (“Strike-zone virtual imaging in real-time by mapping the strike zone in real time using coordinates on the batter and on the home plate” [0095, 0099, 0100, 0105, 0113]), and wherein the ground truth data ([0062]) for identifying home plate is automatically labeled (See Ptucha [0166]). Hall further discloses tracking consecutive frames to identify the baseball in frames following a trajectory ([0025, 0049, 0092, 0094, ball in flight [0095].
Conclusion
16. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is in the Notice of References Cited.
17. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Paul A. D’Agostino whose telephone number is (571) 270-1992.
18. 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.
19. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kang Hu can be reached on (571) 270-1344. The fax phone number for the organization where this application or proceeding is assigned is 571-270-2992.
/PAUL A D'AGOSTINO/Primary Examiner, Art Unit 3715
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