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 .
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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lopez Mendez et al., US 2022/0036577.
Regarding claim 1, Lopez Mendez discloses a processor (para 0007-0008; a processor) comprising: one or more circuits to use one or more neural networks (para 0012; one or more neural networks) to identify a pose of one or more cameras based, at least in part, on one or more different poses of the one or more cameras (fig. 1; para 0006, 0014, and 0053-0054; the one or more neural networks estimating a current camera pose corresponding to a current point in time using a previous camera pose corresponding to a previous point in time, of a camera).
Regarding claim 2, the processor of claim 1, Lopez Mendez further discloses wherein the one or more different poses of the one or more cameras are based on previous identification, by the one or more neural networks, of the one or more different poses of the one or more cameras (para 0006, 0044, and 0053).
Regarding claim 3, the processor of claim 2, Lopez Mendez further discloses wherein the previous identification, by the one or more neural networks, of the one or more different poses of the one or more cameras is based on reception, by the one or more neural networks, of one or more previous images of a sequence of images captured by the one or more cameras (para 0006, 0038, and 0041).
Regarding claim 4, the processor of claim 3, Lopez Mendez further discloses wherein the one or more circuits further use the one or more neural networks to identify the pose of the one or more cameras based, at least in part, on reception, by the one or more neural networks, of a current image of the sequence of images captured by the one or more cameras (para 0006, 0038, and 0041).
Regarding claim 5, the processor of claim 4, Lopez Mendez further discloses wherein the sequence of images comprises a sequence of video frames of a video captured by the one or more cameras, and wherein the current image comprises a current video frame of the video (para 0038).
Regarding claim 6, the processor of claim 5, Lopez Mendez further discloses wherein the one or more circuits further use the one or more neural networks to label the current video frame to indicate the identified pose of the one or more cameras (para 0061 and 0066).
Regarding claim 7, the processor of claim 1, Lopez Mendez further discloses wherein at least an orientation or a position of the one or more cameras according to the identified pose of the one or more cameras is different than at least another orientation or another position of the one or more cameras according to the one or more different poses of the one or more cameras (para 0001, 0035, 0037, 0042, 0044-0046, and 0053; comparing a current camera pose (i.e. a position and orientation of the camera) with previous camera pose to estimate the difference).
Regarding claim 8, this claim recites substantially the same limitations that are performed by claim 1 above, and it is rejected for the same reasons.
Regarding claim 9, this claim recites substantially the same limitations that are performed by claim 2 above, and it is rejected for the same reasons.
Regarding claim 10, this claim recites substantially the same limitations that are performed by claim 3 above, and it is rejected for the same reasons.
Regarding claim 11, this claim recites substantially the same limitations that are performed by claim 4 above, and it is rejected for the same reasons.
Regarding claim 12, this claim recites substantially the same limitations that are performed by claim 5 above, and it is rejected for the same reasons.
Regarding claim 13, this claim recites substantially the same limitations that are performed by claim 6 above, and it is rejected for the same reasons.
Regarding claim 14, this claim recites substantially the same limitations that are performed by claim 7 above, and it is rejected for the same reasons.
Regarding claim 15, this claim recites substantially the same limitations that are performed by claim 1 above, and it is rejected for the same reasons.
Regarding claim 16, this claim recites substantially the same limitations that are performed by claim 2 above, and it is rejected for the same reasons.
Regarding claim 17, this claim recites substantially the same limitations that are performed by claim 3 above, and it is rejected for the same reasons.
Regarding claim 18, this claim recites substantially the same limitations that are performed by claim 4 above, and it is rejected for the same reasons.
Regarding claim 19, this claim recites substantially the same limitations that are performed by claim 5 above, and it is rejected for the same reasons.
Regarding claim 20, this claim recites substantially the same limitations that are performed by claim 6 above, and it is rejected for the same reasons.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Urfalioglu et al., US 2023/0281862 discloses a method estimates a camera pose change estimation.
Jang et al., US 2024/0169562 discloses a device and method with camera pose estimation.
Gu et al., US 2020/0273207 discloses a deep neural network (DNN) system learns a map representation for estimating a camera position and orientation (pose).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VAN D HUYNH whose telephone number is (571)270-1937. The examiner can normally be reached 8AM-6PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Stephen R Koziol can be reached at (408) 918-7630. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/VAN D HUYNH/Primary Examiner, Art Unit 2665
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