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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 09/03/2026 has been entered.
Response to Arguments
Applicant's arguments filed on 09/03/2026 have been fully considered but they are not persuasive.
Regarding section 101, “Claim 1, for example, calls for "a position prediction" which "out of the candidate positions that are calculated" calculates "a position closest to the prior estimation position as the observation prediction position." In doing so, rather than a mere position calculation, claim 1 is directed to a specific prediction position technique …”
Examiner notes that the specific prediction position technique is claimed as a calculation, which is an abstract idea. See Ex parte Desjardins, 2024-000567.
Applicant argues: “Current claim 1 meets the requirements of 2A - Prong Two because the same is integrated into a practical application of improved position prediction that considers among other features, such as posterior estimation position … For example, the claimed invention uses, out of the candidate positions calculated using each observation position”
Examiner notes that while a calculation can be used in a practical application, a calculation itself is not a practical application under the present subject matter eligibility guidelines.
Regarding the newly amended language of Claim 1, Applicant argues: “The combination of Singh and Aomi do not disclose the claimed "tracking of the positioning object based on the predicted posterior estimation position", as currently recited in claim 1.”
Examiner notes that both Singh and Aomi perform object tracking based on future position estimations including intermediate future position estimations embodying the claimed predicted posterior estimation position. See updated reasons for rejection below.
Response to Amendment
Examiner withdraws the rejection of Claims 1, 3, 5-11 under 35 U.S.C. 101, under the “Revised Patent Subject Matter Eligibility Guidance” issued on January 7, 2019 (Federal Register, Vol. 84, No. 4, 50) and in view of “2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence” published on July 17, 2024 (89 FR 58128) and in view of Ex parte Desjardins, 2024-000567. The claims are amended with the step of: “tracking of the positioning object based on the predicted posterior estimation position,” which directs the claimed calculations to a practical application.
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.
The factual inquiries 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.
Claims 1, 3, 5-11 are rejected under 35 U.S.C. 103 as being unpatentable over US 20210341920 to Singh (“Singh”) also cited in an IDS, in view of US 20210357659 to Aomi (“Aomi “) also cited in an IDS.
Regarding Claim 1: “A non-transitory computer-readable storage medium storing therein a position prediction program that causes a computer to execute a process comprising: (See “a non-transitory device on which computer-readable data, programming instructions or both are stored. … "processor" and "processing device" refer to a hardware component of an electronic device that is configured to execute programming instructions” Singh, Paragraphs 71-72.)
calculating, from a position that is on an extended line of a trail of a posterior estimation positions of a positioning object at a plurality of prediction timings in the past, and that is at a distance from the posterior estimation positions at a last prediction timing, to which the positioning object is predicted to advance by a next prediction timing, prior estimation position of the positioning object at a prediction timing; (For example: “For generating predictions and forecasting trajectories [trail lines], the task for the model may be framed as: given the past input coordinates of a vehicle trajectory Vi as Xi=(x',, y, for time steps t={1, . . . , Tabs}, predict the future coordinates Yi=(x',,y,') for time steps {t=Tobs+1, . . . , Tpred}.” Singh, Paragraph 30. In this example, posterior estimation positions can be exemplified by positions from timings t={1, . . . , Tobs}, and a third position can be at one of the prediction timings {t=Tobs+1, . . . , Tpred}.)
calculating, based on the posterior estimation position at the last prediction timing out of the plurality of prediction timings and an observation position that is in real space of the positioning object … an observation prediction position of the positioning object at the prediction timing; (For example: “For generating predictions and forecasting trajectories, the task for the model may be framed as: given the past input coordinates of a vehicle trajectory Vi as Xi=(x',, y, for time steps t={1, . . . , Tabs}, predict the future coordinates Yi=(x',,y,') for time steps {t=Tobs+1, . . . , Tpred}.” Singh, Paragraph 30. In this example, posterior estimation position at the last prediction timing can be exemplified by a position at a time such as Tabs-1, a observation position can be at a later time such as Tabs, and the fourth position can be at one of the prediction timings {t=Tobs+1, . . . , Tpred}.)
[observation position of the positioning object] calculated from image data received from a shooting device after the last prediction timing, (“The perception data may include information relating to one or more objects in the environment of the autonomous vehicle 101. For example, the perception subsystem 122 may process sensor data (e.g., LiDAR or RADAR data, camera images, etc.) in order to identify objects … the perception subsystem may also determine [calculate], for one or more identified objects in the environment, the current state of the object. The state information may include, without limitation, for each object: current location;” which exemplifies a observation position. See Singh, Paragraph 26.)
wherein the calculating of the observation prediction position includes: … in a case in which a plurality of the observation positions are calculated between after the last prediction timing and the prediction timing, calculating each of candidate positions of the positioning object at the prediction timing by using each of a plurality of the observation positions that have been calculated, and (For example: “For generating predictions and forecasting trajectories, the task for the model may be framed as: given the past input coordinates of a vehicle trajectory Vi as Xi=(x',, y, for time steps t={1, . . . , Tabs},” in Singh, Paragraph 30. In this example the fifth positions can correspond to observation positions at timings in the range t={1, . . . , Tabs}.)
out of the positions that are calculated, calculating a position closest to the prior estimation position as the observation prediction position.” (Under the broadest reasonable interpretation consistent with the specification and ordinary skill in the art, the similarity between the prior estimation position and the observation prediction positions is that they are claimed as “positioning object at the prediction timing,” therefore the predetermined condition for the observation prediction position can be the same timing. In Sing, Paragraph 30, this can be exemplified by the positions calculated at Tabs.)
“predicting a position partway between the prior estimation position and the observation prediction position as the posterior estimation position at the prediction timing, (Singh Paragraph 30 indicates that “second” positions at future prediction timings {t=Tobs+1, . . . , Tpred} can be predicted based on any prior prediction “third and fourth” positions at previous prediction timings t={1, . . . , Tobs}, with {Tobs+1, ... ,Tpred-1} representing intermediate / posterior estimation positions that are partway between prior estimation positions and a final / observation estimation position.
Cumulatively, Aomi teaches another possible embodiment, where the position determinations that were determined previously can be used to produce other position determinations using filters in the context of tracking an object over time based on previously determined tracking results: “The searching area setting unit 112 may predict the motion of each object using the motion model of the corresponding object calculated from the past tracking result. … In some embodiments, the predicted position may be included in the tracking information. The integral tracking unit 200 may include the value which is obtained using a Kalman filter” Aomi, Paragraphs 84-86. In these cases, the order of position determinations does not need to correspond to the order in which the object occupied those positions; thus the predicted position can be partway between an observation position and another prediction position.
Therefore, before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to supplement the teachings of Singh to predict a posterior estimation position at some timing from third and fourth positions having a different timing, in the manner taught in Aomi, in order to “calculate the predicted position in consideration of time differences between the current time and the times of the past frames.” Aomi, Paragraphs 84-86 and Singh, Paragraph 30.
Finally, in reviewing the present application, there does not seem to be objective evidence that the claim limitations are particularly directed to: addressing a particular problem which was recognized but unsolved in the art, producing unexpected results at the level of the ordinary skill in the art, or any other objective indicators of non-obviousness.
“tracking of the positioning object based on the predicted posterior estimation position,” (“The perception subsystem 122 may use any now or hereafter known object recognition algorithms, video tracking algorithms, and computer vision algorithms ( e.g., track objects frame-to-frame iteratively over a number of time periods) to determine the perception.” Singh, Paragraph 25. Singh Paragraph 30 indicates that “second” positions at future prediction timings {t=Tobs+1, . . . , Tpred} can be predicted based on any prior prediction “third and fourth” positions at previous prediction timings t={1, . . . , Tobs}, with {Tobs+1, ... ,Tpred-1} representing positions tracked at intermediate / posterior estimation positions that are partway between prior estimation positions and a final / observation estimation position.
See a similar embodiment of future position estimation based on past positions using a Kalman filter, including predicting positions part way between an observation position and another prediction position in Aomi, Paragraphs 84-86. See statement of motivation above.)
Regarding Claim 3: “The non-transitory computer-readable storage medium storing therein the position prediction program according to claim 1, wherein the calculating of the observation prediction position includes, in a case in which the observation position is calculated before a predetermined amount of time elapses from the last prediction timing, calculating the observation prediction position based on the posterior estimation position at a timing earlier than the last prediction timing out of the plurality of prediction timings and the observation position.” (Under the broadest reasonable interpretation consistent with the specification and ordinary skill in the art, positions at an earlier time can be calculated based on input positions determined at respectively earlier times. Singh teaches: “For generating predictions and forecasting trajectories, the task for the model may be framed as: given the past input coordinates of a vehicle trajectory Vi as Xi=(x',, y, for time steps t={1, . . . , Tobs}, predict the future coordinates Yi=(x',,y,') for time steps {t=Tobs+1, . . . , Tpred}.” Singh, Paragraph 30. In this case if Tobs-1 represents the current frame instead of Tobs, then the entire notation can be represented with “-1” to perform the same prediction method for a frame at an earlier time.)
Claim 5 is rejected for reasons stated for Claims 1 and 3.
Claim 6 “An information processing device,” is rejected for reasons stated for Claim 1, and because the prior art teaches: “a memory; and a processor coupled to the memory and the processor configured to: …” (See “The terms "memory," "memory device," "data store," "data storage facility" and the like each refer to a non-transitory device on which computer-readable data, programming instructions or both are stored. … "processor" and "processing device" refer to a hardware component of an electronic device that is configured to execute programming instructions” Singh, Paragraphs 71-72.)
Claim 7 is rejected for reasons stated for Claim 5 in view of the Claim 6 rejeciton.
Claim 8 is rejected for reasons stated for Claims 6, 1 and 3.
Claim 9, “A position prediction method,” is rejected for reasons stated for Claim 1, because the medium of claim 1 implements the steps of Claim 9.
Claim 10 is rejected for reasons stated for Claim 3 in view of the Claim 9 rejection.
Claim 11 is rejected for reasons stated for Claims 9, 1 and 3.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20160035098 to Ikoma (“Ikoma”) teaching a technique for estimating the state of an observable event using time-series filtering, and particularly to, for example, a technique for tracking objects in moving images using time-series filtering.
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/MIKHAIL ITSKOVICH/Primary Examiner, Art Unit 2483
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