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 . Claims 1-20 have been examined.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d).
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 05/13/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Claims 1-20 are directed toward a device, method and program. Therefore, it can be seen that they fall within one of the four statutory categories of invention. However, the claims clearly do not meet the three-prong test for patentability.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and/or
Mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion).
Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 1 recites:
An information processing device comprising:
a parking spot analysis unit configured to execute analysis processing on a parking spot included in an image, wherein the parking spot analysis unit
estimates a parking spot definition rectangle indicating a parking spot region in the image, by using a learning model generated in advance.
The examiner submits that the foregoing bold limitation(s) constitute a “mental process” and/or “certain methods of organizing human activity” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “estimates a parking spot definition rectangle indicating a parking spot region in the image” in the context of this claim encompasses the user mentally analyzing the data and determining a parking spot definition rectangle. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrated the abstract idea into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea , adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
An information processing device comprising:
a parking spot analysis unit configured to execute analysis processing on a parking spot included in an image, wherein the parking spot analysis unit:
estimates a parking spot definition rectangle indicating a parking spot region in the image, by using a learning model generated in advance.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “by using a learning model generated in advance”, the examiner submits that these limitations are mere data gathering in conjunction with a law of nature or abstract ideal (MPEP § 2106.05). In particular, “by using a learning model generated in advance” indicate pre-solution activity such that it amounts no more than a step of gathering data for use in a claimed process. Lastly, the “a parking spot analysis unit” recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing data. This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis - Step 2B
Regarding Step 2B of the 2019 PEG, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using one or more processors to perform the determining ... amounts to nothing more than applying the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “by using a learning model generated in advance”, the examiner submits that these limitations are insignificant extra-solution activities as previously discussed.
Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well- understood, routine, conventional activity in the field. The additional limitations of “location data received from a user device of a user” are well-understood, routine, and conventional activities because the specification does not provide any indication that the user device is anything other than a conventional computer. MPEP 2106.05(d)(II), and the cases cited therein including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), 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. Hence, the claim is not patent eligible.
Dependent claims 2-18 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application (i.e., further characterizing the receipt of data and the mental processes). Therefore, dependent claims 2-18 are not patent eligible under the same rationale as provided for in the rejection of independent claims 1 and 19-20.
Therefore, claims 1-20 are ineligible under 35 USC §101.
Claim 20 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. In regards to claim 20, applicant is claiming a program for carrying out the method according to claim 19. A computer program, when it is not part of a system or a non-transitory computer readable medium, can be encoded on a non-statutory transitory form of signal transmission, such as a propagating electrical or electromagnetic signal. As such, it does not fall into one of the four categories of patent-eligible subject matter: process, machine, manufacture or composition matter.
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 (i.e., changing from AIA to pre-AIA ) 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 1-4 and 16-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Tanigawa et al. (US 10,650,681 B2) (Tanigawa hereinafter).
Regarding claim 1, Tanigawa discloses an information processing device comprising:
a parking spot analysis unit configured to execute analysis processing on a parking spot included in an image, wherein the parking spot analysis unit estimates a parking spot definition rectangle indicating a parking spot region in the image, by using a learning model generated in advance (Col. 3, lines 17-38, a parking position identification method according to one aspect of the present disclosure is a parking position identification method in which at least one computer identifies a parking position of a target vehicle, the parking position identification method including: acquiring input data as an image that is generated by photographing a parking region by a camera which is installed in the target vehicle; and identifying the parking position of the target vehicle in the photographed parking region by inputting the input data to a learning model that indicates a relationship between a parking region which has a width in which parking of at least one vehicle is feasible and a parking position for one vehicle in the parking region).
Regarding claim 2, Tanigawa discloses the information processing device according to claim 1, as stated above, wherein the parking spot analysis unit estimates an entrance direction of the parking spot in the image by using the learning model (Col. 4, lines 52-65, the second annotation may indicate parallel parking or side-by-side parking as the parking state in the parking position for one vehicle, and in the identifying of the parking position of the target vehicle, the input data may be input to the learning model to identify parallel parking or side-by -side parking as the parking state in the parking position of the target vehicle. Further, the second annotation may indicate forward entrance or rearward entrance as the parking state in the parking position for one vehicle, and in the identifying of the parking position of the target vehicle, the input data may be input to the learning model to identify forward entrance or rearward entrance as the parking state in the parking position of the target vehicle).
Regarding claim 3, Tanigawa discloses the information processing device according to claim 1, as stated above, wherein the parking spot analysis unit estimates whether a parking spot in the image is a vacant parking spot in which no parked vehicle is present or an occupied parking spot in which a parked vehicle is present, by using the learning model (Col. 6, line 58 – col. 7, line 10).
Regarding claim 4, Tanigawa discloses the information processing device according to claim 1, as stated above, wherein the parking spot analysis unit estimates a spot center that is a center position of a parking spot in the image by using the learning model (Fig. 7 is a diagram for explaining one example of effects by the parking position identification system).
Regarding claim 16, Tanigawa discloses the information processing device according to claim 1, as stated above, wherein the information processing device further includes: a display control unit configured to generate display data for a display unit, and the display unit generates display data in which identification data analyzed by the parking spot analysis unit is superimposed on the image, and outputs the display data to the display unit (Col. 10, lines 28-61).
Regarding claim 17, Tanigawa discloses the information processing device according to claim 1, as stated above, wherein the display control unit generates display data in which at least one piece of identification data is superimposed on a parking lot image, and outputs the display data to the display unit, the identification data including: (a) a vacant parking spot identification frame; (b) an occupied parking spot identification frame; (c) a parking spot entrance direction identifier; and (d) a parking spot state (vacant/occupied) identification tag (Col. 11, lines 10-54).
Regarding claim 18, Tanigawa discloses the information processing device according to claim 1, as stated above, wherein the information processing device further includes: an automated driving control unit, and the automated driving control unit is input with analysis information generated by the parking spot analysis unit, to execute automated parking processing (Col. 10, line 62 – col. 11, line 6; col. 13, lines 17-23).
Regarding claim 19, the elements contained in claim 19 are substantially similar to elements presented in claim 1, except that it set forth the claimed invention as a method rather than a device and is rejected for the same reasons as applied above.
Regarding claim 20, the elements contained in claim 20 are substantially similar to elements presented in claim 1, except that it set forth the claimed invention as a program rather than a device and is rejected for the same reasons as applied above.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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 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.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Tanigawa in view of Liu et al. (US 2022/0392127 A1) (Liu hereinafter).
Regarding claim 5, Tanigawa discloses the information processing device according to claim 4, as stated above, except for “the parking spot analysis unit estimates the spot center by using CenterNet as the learning model”.
Liu teaches such claimed subject matter (Abstract). Liu teaches that “a trained deep learning model is used to infer the adjusted image and automatically generate annotations in order to provide more accurate predicted results. The deep learning model can be a Region-based Convolutional Neural Networks (R-CNN) model, a You Look Once (YOLO) model, a Single-Shot Multibox Detector (SDD) model, a CenterNet model, a Neural Architecture Search (NAS) model, or any other appropriate deep learning model” ([0026]).
Therefore, it would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to include the deep learning model taught by Liu into the invention of Tanigawa so that the labor cost and the time cost of the image annotation method are reduced, and the image annotation task is simplified.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Tanigawa in view of Tang et al. (CN 111797715 A) (Tang hereinafter).
Regarding claim 6, Tanigawa discloses the information processing device according to claim 4, as stated above, except for “the parking spot analysis unit generates a spot center identification heat map for estimating a spot center that is a center position of a parking spot in the image by using the learning model, and estimates the spot center by using the generated spot center identification heat map”.
Tang teaches such claimed subject matter (Abstract). Tang teaches “generating a heat map for identifying a section center for estimating the center position of a parking section in an image, and it can be said that it would have been easily accomplished by a person skilled in the art to adapt the learning model of the invention described in Tanigawa to generate a heat map for identifying a section center for estimating the center position of a parking section in an image, which is the central position of a parking section in an image, as described in Tang, and to estimate the section center using the heat map” ([0071]).
Therefore, it would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to include the heat map taught by Tang into the invention of Tanigawa to estimate the center position of a parking section to improve the efficiency of the parking space detection.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Tanigawa in view of Tanimichi et al. (WO 2006/064544 A1) (Tanimichi hereinafter).
Regarding claim 9, Tanigawa discloses the information processing device according to claim 1, as stated above, except for “the parking spot analysis unit includes: a spot center grid estimation unit configured to estimate a spot center on a grid basis by using the learning model, the spot center being a center position of a parking spot in the image”.
Tanimichi teaches such claimed subject matter (Abstract). Tanimichi teaches that “the parking space center, which is the central position of the parking space in the image, is estimated in grid units” (Fig. 5).
Therefore, it would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to include the grid units taught by Tanimichi into the learning model of Tanigawa to estimate the parking space center, which is the central position of the parking space in the image .
Allowable Subject Matter
Claims 7-8 and 10-15 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.
Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. See attached form PTO-892.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Luke Huynh whose telephone number is 571-270-5746. The examiner can normally be reached Mon 8-5, Tues 8-12, Thurs & Fri 8-2.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hitesh Patel can be reached at 571-270-5442. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/LUKE HUYNH/Primary Examiner, Art Unit 3667
02/17/2026