DETAILED ACTION
Status
This Office Action is responsive to claims filed on 03/28/2025. Please note Claims 1-20 are pending and have been examined.
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 Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “a three-dimensional (3D) Gaussian distribution generator” and “an inverse camera projector” in claims 1-13.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-13 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim(s) 1-13 has/have been interpreted to cover the corresponding structure described in the specification that achieves the claimed function and equivalents thereof, since the claim limitation(s) invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the specification fails to disclose specific structures or algorithms for the recited “three-dimensional (3D) Gaussian distribution generator” and “inverse camera projector”. It is impossible to determine the equivalents of the claimed “three-dimensional (3D) Gaussian distribution generator” and “inverse camera projector”, as required by 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
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 of this title, 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.
Claims 1, 5-7, 9-18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over NALLABOLU (US 20250086889 A1), in view of B. Kerbl, et al., "3D Gaussian Splatting for Real-Time Radiance Field Rendering" (hereinafter “Kerbl”).
Regarding Claim 1, NALLABOLU discloses a three-dimensional Gaussian splatting (3DGS) system comprising:
a three-dimensional (3D) Gaussian distribution generator ([0095] “In one or more examples, the one or more processors can generate a Gaussian distribution of the depth prediction values.”); and
an inverse camera projector configured to un-project pixels from image planes to 3D Gaussians in camera space at expected un-projected ray depth positions ([0094] “At block 860 of the block integration unit 810, the one or more processors can unproject the depth prediction values at the pixel values (e.g., x,y values) onto a 3D space to obtain 3D points (e.g., which are 3D coordinates, such as x,y,z) of the depth prediction values in the 3D space”).
NALLABOLU does not expressly name the unprojected 3D points with Gaussian distributed depth prediction values (see [0095] “At block 870 of the block integration unit 810, the one or more processors may remove outlier depth prediction values from the depth prediction values.”) as 3D Gaussians.
However, in the same field of endeavor, Kerbl discloses an inverse camera projector configured to un-project pixels from image planes to 3D Gaussians in camera space at expected un-projected ray depth positions (page 2, left column, “We first introduce 3D Gaussians as a flexible and expressive scene representation. We start with the same input as previous NeRF-like methods, i.e., cameras calibrated with Structure-from-Motion (SfM) [Snavely et al. 2006] and initialize the set of 3D Gaussians with the sparse point cloud produced for free as part of the SfM process.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified the system of NALLABOLU with the feature of initializing 3D Gaussians from images. Doing so could offer “a flexible and expressive scene representation”, as taught by Kerbl.
Regarding Claim 5, NALLABOLU-Kerbl discloses the system of claim 1, configured to apply gradient descent to configure camera space center points for the 3D Gaussians, based on a distribution of the 3D Gaussians in a camera space at expected un-projected ray depth positions (Kerbl, page 5, left column, “We use Stochastic Gradient Descent techniques for optimization, taking full advantage of standard GPU-accelerated frameworks, and the ability to add custom CUDA kernels for some operations, following recent best practice [Fridovich-Keil and Yu et al. 2022; Sun et al. 2022].”).
Regarding Claim 6, NALLABOLU-Kerbl discloses the system of claim 1, configured to apply gradient descent to configure camera space covariant matrices for the 3D Gaussians (Kerbl, page 4, right column “For our optimization of all our parameters, we use gradient descent that cannot be easily constrained to produce such valid matrices, and update steps and gradients can very easily create invalid covariance matrices.”).
Regarding Claim 7, NALLABOLU-Kerbl discloses the system of claim 1, configured to filter out 3D Gaussians smaller than pixel sizes according to a variance of an applied low-pass kernel (NALLABOLU [0095] “The one or more processors can calculate a variance, and can filter out depth prediction values that exceed a variance threshold (e.g., a three sigma value). In one or more examples, the one or more processors can filter out depth prediction values based on a calculated mean or median point of the depth prediction values.”).
Regarding Claim 9, NALLABOLU-Kerbl discloses the system of claim 7, further comprising a training objective configured to regularize the 3D Gaussians to a similar appearance before and after the low-pass kernel is applied (NALLABOLU [0116] “In some aspects, the computing device (or component thereof) can remove outlier depth prediction values from the depth prediction values based on a variance of the depth prediction values.” Kerbl, page 2, right column, “The success of NeRF has resulted in an explosion of follow-up methods that address quality and speed, often by introducing regularization strategies; the current state-of-the-art in image quality for novel-view synthesis is Mip-NeRF360 [Barron et al. 2022].”).
Regarding Claim 10, NALLABOLU-Kerbl discloses the system of claim 1, further configured with a maximum blending weight to measure the contribution of each 3D Gaussian to training views (NALLABOLU [0096] “The one or more processors may then assign weights (e.g., each a SFD fusion weight, such as a sample.cur_weight), which may be gradient weights, to the remaining depth prediction values, based on their respective estimated confidence level, to produce weighted depth prediction values.”).
Regarding Claim 11, NALLABOLU-Kerbl discloses the system of claim 10, further configured to prune 3D Gaussians for which the contribution to the training views fails to satisfy a configured threshold (NALLABOLU [0116] “In some aspects, the computing device (or component thereof) can remove outlier depth prediction values from the depth prediction values based on a variance of the depth prediction values” Kerbl, page 5, right column, “we densify every 100 iterations and remove any Gaussians that are essentially transparent, i.e., with 𝛼 less than a threshold 𝜖𝛼.”).
Regarding Claim 12, NALLABOLU-Kerbl discloses the system of claim 1, further configured to duplicate 3D Gaussians comprising a densification priority satisfying a configured threshold (Kerbl, page 5, right column, “Since both cases are good candidates for densification, we densify Gaussians with an average magnitude of view-space position gradients above a threshold 𝜏pos, which we set to 0.0002 in our tests.”).
Regarding Claim 13, NALLABOLU-Kerbl discloses the system of claim 12, further configured to duplicate a top number of the 3D Gaussians having the highest densification priority (Kerbl, page 5, right column, “For small Gaussians that are in under-reconstructed regions, we need to cover the new geometry that must be created. For this, it is preferable to clone the Gaussians, by simply creating a copy of the same size, and moving it in the direction of the positional gradient.”).
Regarding Claim 14, it recites similar limitations of claim 1. The rationale of claim 1 rejection is applied to reject claim 14. Notice that the claimed rendering step is taught by NALLABOLU [0075] “rendering systems infer the position of a voxel based upon its position relative to other voxels (e.g., its position in the data structure that makes up a single volumetric image)”, and Kerbl, Section 5.1, “The optimization is based on successive iterations of rendering and comparing the resulting image to the training views in the captured dataset.”
Regarding Claim 15, it recites similar limitations of claim 1. The rationale of claim 1 rejection is applied to reject claim 15. Notice that the claimed processor and memory is taught by NALLABOLU Fig. 12 and [0123] “In the context of computer instructions, the operations represent computer-executable instructions stored on one or more computer-readable storage media that, when executed by one or more processors, perform the recited operations.”
Regarding Claim 16, NALLABOLU-Kerbl discloses the computer system of claim 15, wherein the data processor is a graphics processing unit (NALLABOLU [0122] “For example, the components can include and/or can be implemented using electronic circuits or other electronic hardware, which can include one or more programmable electronic circuits (e.g., microprocessors, graphics processing units (GPUs)” Kerbl, Section 7.2, “All results are reported running on an A6000 GPU”).
Regarding Claim 17, it recites similar limitations of claim 5. The rationale of claim 5 rejection is applied to reject claim 17.
Regarding Claim 18, it recites similar limitations of claim 7. The rationale of claim 7 rejection is applied to reject claim 18.
Regarding Claim 20, it recites similar limitations of claim 11. The rationale of claim 11 rejection is applied to reject claim 20.
Allowable Subject Matter
Claim 19 is 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
SHIN (US 20250240452 A1) – This reference teaches an image encoding method including: deriving coefficients of a spherical harmonic function for a plurality of vertices on a three-dimensional space; generating a plurality of layer images based on the coefficients; and encoding the plurality of layer images. In this case, each of the plurality of layer images may include a coefficient value in order corresponding to the spherical harmonic function.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHONG WU whose telephone number is (571)270-5207. The examiner can normally be reached MON-FRI: 9AM-5PM EST.
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/CHONG WU/Primary Examiner, Art Unit 2613
