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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 06/18/2024, 10/11/2024, and 09/05/225 were filed after the mailing date of the application. The submission 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 § 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 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, 13-15, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Sharma et al. (US. Patent App. Pub. No. 2016/0127724, “Sharma”, hereinafter).
As per claim 1, Sharma teaches a computer-implemented image processing method comprising:
obtaining a plurality of images, each of the plurality of images comprising a first view of a scene (¶ [10]);
computing respective scores for each of the plurality of images (¶ [42], computing the match score of each image);
estimating respective camera poses of each of the plurality of images (¶ [28] referring to Fig. 2);
using the computed scores and the estimated camera poses to determine a new camera pose useable for generating a new image comprising a second view of the scene and having a score greater than a first threshold score (¶ [40-42].
Sharma does not expressly teach generating the new image using the new camera pose. However, Sharma does teach selecting the camera pose as current or from the image library for capturing image (¶ [10]) after the image score and the camera pose estimation is done (¶ [40-42], implying a currently generated camera pose from the estimated camera pose). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of determining camera pose taught by Sharma as new camera pose for generating new image, the advantage of which is to eliminate invalid camera pose (¶ [43]).
As per claim 13, as addressed in claim 1, Sharma impliedly teaches determining whether at least one of the computed scores is greater than the first threshold score (see claim 1),
if at least one of the computed scores is greater than the first threshold score then outputting the image of the plurality of images having the score greater than the first threshold score (¶ [42]), and
if at least one of the computed scores is not greater than the first threshold score then estimating the respective camera pose of each of the plurality of images (¶ [43]).
Claim 14, which is similar in scope to claim 1 as addressed above, is thus rejected under the same rationale.
Claim 15, which is similar in scope to claim 1 as addressed above, is thus rejected under the same rationale.
Claim 20, which is similar in scope to claim 13 as addressed above, is thus rejected under the same rationale.
Claims 2, 3, 12, 16, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Sharma et al. (US. Patent App. Pub. No. 2016/0127724) in view of Wang et al. (US. Patent App. Pub. No. 20220301252, “Wang”).
As per claim 2, Sharma does not expressly teach wherein the computed scores are computed using a scoring model comprising a trained machine learning model, and the computed scores represent a characteristic of an image. However, Sharma does teach the computed scores represent a characteristic of an image (see ¶ [42], i.e., representing the features of the image).
However, in a similar method of generating new camera pose (see ¶ [6-9]), Wang teaches training the input images using deep neural network (¶ [6-9]), wherein the score is computed based on the machine learning (¶ [111]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the method as taught by Wang to the method as taught by Sharma as addressed above, the advantage is to predict the correct appearance of the image from the requested pose and/or time (¶ [28]).
As per claim 3, the combined teachings of Sharma and Wang also include wherein the computed scores represent the characteristic comprising at least one of a level of noise of an image, a level of blurring of the image, or a quality of the image based on an extent to which the image complies with universal photograph composition rules (Sharma, ¶ [28], and ¶ [42]).
As per claim 12, the combined Sharma-Wang does also teach wherein the generating the new image using the new camera pose is performed using a machine learning model, wherein the machine learning model comprises a Neural Radiance Field, NeRF, model trained using training data comprising camera poses and images to output an image rendered based on an input camera pose (see Wang, ¶¶ [47-48], and [50]). Thus, claim 12 would have been obvious over the combined references for the reason above.
Claim 16, which is similar in scope to claim 2 as addressed above, is thus rejected under the same rationale.
Claim 19, which is similar in scope to claim 12 as addressed above, is thus rejected under the same rationale.
Claims 4 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Sharma et al. (US. Patent App. Pub. No. 2016/0127724) in view of Gong et al. (US. Patent App. Pub. No. 2021/0003684, “Gong”).
As per claim 4, Sharma does teach:
…find a camera pose amongst the estimated camera poses associated with the computed score greater than a second threshold score,
selecting the camera pose found to have the computed score greater than the second threshold score as an initial camera pose for use in the determining the new camera pose, and
if the computed scores are not greater than the second threshold score then selecting a random camera pose as the initial camera pose for use in the determining the new camera pose (See claim 1, referring to ¶ [42-43], referring to Fig. 2).
Sharma does not expressly teach applying a pattern recognition process to the estimated camera poses and the computed scores to find a camera pose.
However, in a similar method of generating camera pose (¶ [107-110]), Gong teaches the above feature, i.e., applying a pattern recognition process to the estimated camera poses and the computed score to find a camera pose (see ¶ [122], and also ¶ [127-129]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the method as taught by Gong into the method as taught by Sharma as addressed above, the advantage of which is to determine if the camera is sufficiently focused (¶ [122]).
Claim 17, which is similar in scope to claim 4 as addressed above, is thus rejected under the same rationale.
Allowable Subject Matter
Claims 5-11 and 18 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.
The following is a statement of reasons for the indication of allowable subject matter: The prior art taken singly or in combination does not teach or suggest, a computer-implemented image processing method, among other things, comprising:
…rendering an image using the initial camera pose, the rendered image having a resolution lower than a resolution of the obtained plurality of images;
computing a score for the low resolution image using the scoring model;
determining whether the computed score of the low resolution image is greater than the first threshold score;
if the computed score of the low resolution image is greater than the first threshold score then outputting the camera pose used to generate the low resolution image as the new camera pose; and
if the computed score of the low resolution image is not greater than the first threshold score then seeking a candidate new camera pose.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Hau H. Nguyen whose telephone number is: 571-272-7787. The examiner can normally be reached on MON-FRI from 8:30-5:30.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tammy Goddard, can be reached on (571) 272-7773.
The fax number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HAU H NGUYEN/Primary Examiner, Art Unit 2611