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 .
Response to Amendment
The Amendment filed on November 7, 2025 has been entered. Claims 1–12 are currently pending. Claims 1, 11, and 12 have been amended.
Response to Arguments
Applicant’s arguments filed November 7, 2025 have been fully considered. The arguments are persuasive in part with respect to the prior interpretation under 35 U.S.C. § 112(f) and the previous rejections under 35 U.S.C. § 103. Applicant’s arguments are not persuasive with respect to the rejection of claim 12 under 35 U.S.C. § 101, as explained below.
Applicant’s arguments regarding claim 12, see page 6 of the Remarks, are not persuasive. Applicant argues that claim 12 has been amended to recite a “non-statutory computer readable medium” and is therefore directed to statutory subject matter. The amended language does not recite a “non-transitory” computer-readable medium or otherwise exclude transitory propagating signals from the scope of the claim. Moreover, the phrase “non-statutory computer readable medium” affirmatively characterizes the recited medium as non-statutory and does not identify a recognized statutory class under 35 U.S.C. § 101. Merely changing the claim from a program per se to a broadly recited computer-readable medium does not cure the rejection when the claim continues to encompass non-statutory embodiments. Accordingly, Applicant’s request to withdraw the rejection is denied, and claim 12 remains rejected under 35 U.S.C. § 101 for the reasons set forth in this Office Action.
Applicant’s arguments, see page 6 of the Remarks, state that the amendments replace the previously recited “means” with “circuitry configured to” perform the claimed functions and that the amended claims therefore no longer invoke 35 U.S.C. § 112(f). The Examiner agrees that amended claim 11 recites circuitry configured to perform the claimed operations rather than a means-plus-function limitation. Accordingly, the prior interpretation of claim 11 under 35 U.S.C. § 112(f) is withdrawn.
Applicant’s arguments, see pages 1–2 of the Remarks, regarding the previous rejections under 35 U.S.C. § 103 are persuasive with respect to the particular combinations previously applied. Upon reconsideration, the Examiner agrees that the previously cited portions of Huebner and Suzuki do not disclose or suggest the complete optimizing sequence newly added to independent claim 1. Claims 11 and 12 contain substantially corresponding amendments. Accordingly, the previous rejections of claims 1, 3–4, 6–9, and 11–12 under 35 U.S.C. § 103 as unpatentable over Huebner in view of Suzuki; claim 2 over Huebner in view of Suzuki and Yano; claim 5 over Huebner in view of Suzuki and Hashimoto; and claim 10 over Huebner in view of Suzuki and Wang are withdrawn.
However, a new ground of rejection under 35 U.S.C. § 103 is made in this Office Action applying Sung in view of Besl and the previously cited references to address the newly added iterative optimization and convergence limitations of amended claims 1, 11, and 12. This modification to the rejection is directly necessitated by Applicant’s amendment adding new limitations to the independent claims. Applicant’s amendments to claims 1, 11, and 12 have been fully considered. The newly added limitations of the amended independent claims have been considered and addressed in the updated rejections utilizing newly cited prior art. Because the necessity to apply new references to the independent claims, and the withdrawal and replacement of the prior grounds of rejection, were directly necessitated by Applicant’s substantive amendments adding new limitations, this action is properly made final in accordance with MPEP § 706.07(a).
Based on these facts, this action is made FINAL.
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1–12 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Independent claims 1, 11, and 12 recite, in relevant part, “identifying a shape of each of the plurality of components when the calculated amount of change in the evaluation value has converged within a predetermined range”.
The originally filed disclosure does not reasonably convey to one of ordinary skill in the art that Applicant was in possession of identifying the component shapes in response to convergence of an amount of change in the evaluation value.
Paragraph [0090] describes calculating an amount of change in an evaluation value while changing each optimization parameter from an initial value. Paragraph [0091] describes updating the parameter based on a gradient vector calculated in step S903. Paragraph [0092], however, expressly describes determining whether “the amount of change in the parameter has converged within a predetermined range” or whether the number of parameter updates has reached a predetermined threshold. Paragraph [0092] does not describe determining convergence of an amount of change in the evaluation value.
Although step S905 of Figure 9 generally asks whether an “amount of change” has converged, paragraph [0092], which describes step S905, identifies the converging quantity as the amount of change in the parameter. The disclosure therefore distinguishes the change in the evaluation value calculated in step S903 from the change in the parameter evaluated for convergence in step S905. In other words, the specification consistently discloses that the optimization loop terminates when the amount of change in the parameter (i.e., the size, position, or angle of the boundary frame) has converged, or when a maximum number of iterations is reached. The specification does not disclose terminating the optimization when the amount of change in the evaluation value itself has converged.
Accordingly, the disclosure does not expressly, implicitly, or inherently support the claimed condition that the calculated amount of change in the evaluation value has converged within a predetermined range.
Claims 2–10 depend directly or indirectly from claim 1 and therefore incorporate the unsupported limitation. Claims 11 and 12 independently recite substantially the same unsupported limitation.
Applicant may wish to consider amending the claims to recite convergence of “the amount of change in the parameter,” consistent with paragraph [0092]. Any amendment must find support in the application as originally filed.
Claim Rejections - 35 USC § 112(b)
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 1-12 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Independent claim 1 recites: “setting an initial value of a parameter in accordance with the estimated at least one boundary frame”, “calculating an evaluation value using an evaluation function”, and “calculating an amount of change in the evaluation value based on the initial value and the evaluation value”.
The scope of “calculating an amount of change in the evaluation value based on the initial value and the evaluation value” is unclear. In the preceding limitation, “the initial value” is an initial value of the parameter, whereas “the evaluation value” is an output of the evaluation function. The claim does NOT specify the mathematical or functional relationship by which an amount of change in the evaluation value is calculated from these two different quantities. In particular, the claim does not make clear whether the recited “amount of change” is:
a difference between two evaluation values;
a rate of change of the evaluation value with respect to the parameter;
a gradient vector of the evaluation function;
an amount by which the parameter is changed; or
some other quantity derived from the initial parameter value and the evaluation value.
The claim does not expressly recite a second evaluation value, changing or perturbing the parameter, a parameter interval, or calculating a gradient with respect to the parameter. Consequently, one of ordinary skill in the art cannot determine with reasonable certainty what calculation satisfies the limitation.
The subsequent limitations do not resolve the ambiguity. Claim 1 further recites “updating the parameter based on the calculated amount of change in the evaluation value” and identifying the component shapes “when the calculated amount of change in the evaluation value has converged within a predetermined range”. Because the claimed “amount of change” is not clearly defined, it is likewise unclear what quantity controls the parameter update and what quantity must converge.
The written description further illustrates the ambiguity. Figure 9 and paragraphs [0090]-[0091] describe calculating a “gradient vector” by changing each optimization parameter at predetermined intervals from an initial value and then updating the parameter based on that gradient vector. Paragraph [0092], however, describes terminating the optimization when an amount of change in the parameter, not an amount of change in the evaluation value, has converged. The claims do not clearly correspond to either the disclosed gradient-vector calculation or the disclosed parameter-change convergence criterion. The specification at paragraph [0090] describes calculating the amount of change of the evaluation value while changing the parameter from its initial value. The current claim language fails to clearly capture this relationship.
Independent claims 11 and 12 contain substantially the same indefinite limitations and are rejected for the same reasons. Dependent claims 2-10 incorporate the indefinite subject matter of claim 1 and do not further limit the claims in a manner that resolves the ambiguity. Accordingly, claims 2-10 are also rejected under 35 U.S.C. 112(b).
To advance prosecution, and assuming that applicant intends to claim the gradient-based optimization described in Figure 9 and paragraphs [0090-0092], applicant may consider amending the relevant limitations to recite: “calculating a gradient vector representing a rate of change of the evaluation value with respect to the parameter by changing the parameter at predetermined intervals from the initial value”, “updating the parameter based on the calculated gradient vector”, and “identifying a shape of each of the plurality of components when an amount of change in the parameter has converged within a predetermined range”.
Or the best wording capturing both disclosures is: “calculating a rate of change in the evaluation value with respect to the parameter by varying the parameter from the initial value;”.
Claims 3-5, and 8-9 recite the limitation "the boundary frame" . However, there is insufficient antecedent basis for this term in the claims. Independent claim 1 recites "at least one boundary frame", the phrase permits the estimation of more than one boundary frame. When claim 1 encompasses multiple boundary frames, the recitation “the boundary frame” in claims 3-5, and 8-9 identify single “the boundary frame”. To overcome this rejection, Applicant should amend the dependent claims to recite "the at least one boundary frame".
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.
Claim 12 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter because the claim recites “A non-statutory computer readable medium storing thereon a program...”. While the Examiner understands this is likely a typographical error for "non-transitory", the claim as currently written explicitly recites a "non-statutory" medium. By definition, subject matter that is "non-statutory" does not fall within one of the four statutory categories of invention (process, machine, manufacture, or composition of matter) set forth in 35 U.S.C. 101.
Applicant is required to amend the claim preamble to recite "A non-transitory computer readable medium" to properly claim a tangible article of manufacture.
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 1-4, 8-9 and 11-12 are rejected rejected under 35 U.S.C. §103 as being unpatentable over Sung (Sung et al, Data-driven structural priors for shape completion. ACM Transactions on Graphics, 34(6), 1–11., 2015), in view of Besl (Besl et al, "A method for registration of 3-D shapes," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 239-256, 1992).
Regarding claim 1, Sung teaches a workpiece measurement method for measuring a shape and a position of a workpiece constituted of a plurality of components ( [Pages. 1–3], [Figs. 1–2], [Sec. 1 and 3]: Sung teaches analyzing an incomplete 3D scan of an object constituted of multiple parts. Sung estimates a part-based structure including the presence, label, position, size, and orientation of the respective parts. The parts include, for example, the seat, back, legs, and armrests of a chair or the respective components of an airplane or bicycle. Accordingly, Sung’s method measures the shape and position of an object constituted of a plurality of components. ), the workpiece measurement method comprising:
an acquiring step for acquiring three-dimensional point cloud data of the workpiece;
( [Sec. 3.1]: Sung receives an incomplete three-dimensional point scan of an object as input. Sung explains that real scans are acquired using a Kinect scanner and that the resulting foreground scan is represented as a three-dimensional point cloud (P). )
an outline estimating step for estimating at least one boundary frame indicating an outline corresponding to each of the plurality of components by using the point cloud data and a condition defined in correspondence with the shape of the workpiece serving as a measurement target; and
( [Figs. 1–2], [Sec. 3], [Sec. 4.1]: Sung teaches estimating a part structure from the input point cloud. Each detected part (b) is represented by an oriented box having rotation (Rb), translation (tb), and anisotropic scale (sb). The scaled, rotated, and translated box defines a three-dimensional boundary enclosing and indicating the outline of its corresponding part. Sung further teaches that structural priors are trained independently for each object or shape category and capture the expected presence, position, orientation, scale, and relationships of the parts associated with that category. The category-specific structural prior is therefore a condition defined in correspondence with the shape of the object serving as the measurement target. Sung uses the input point cloud together with this condition to estimate an oriented boundary box for each component. )
an optimizing step for optimizing the at least one boundary frame estimated in the outline estimating step by:
setting an initial value of a parameter in accordance with the estimated at least one boundary frame,
( [Fig. 4], [Sec. 4.3 > Initialization]: Sung initializes the optimization by classifying points, dividing the classified points into connected components, and fitting an oriented box to each connected component. Each fitted box supplies an initial candidate part representation (Θ^cand). The parameters of each representation include its rotation, translation, and scale. Sung therefore teaches setting initial values of boundary-frame parameters in accordance with an initially estimated oriented boundary box. )
calculating an evaluation value using an evaluation function,
( [Eqs. (1)–(12)]: Sung defines an evaluation or energy function that measures how well the estimated part structure represents the input point cloud and complies with the learned structural prior. Sung’s final evaluation function is E = w₁Epnt + w₂Esmooth + w₃ESMD + w₄Epair + w₅Esymm, an evaluation function combining point-classification, smoothness, surface-fitting, part-relation, and symmetry terms. Sung evaluates candidate part arrangements and boundary-box parameters using this energy function and selects or refines lower-energy representations. Accordingly, Sung teaches calculating an evaluation value using an evaluation function. )
calculating an amount of change in the evaluation value based on the initial value and the evaluation value,
( [Sec. 4.3 > Point segmentation, and Part pose optimization], [Eq. (15)]: Sung initializes candidate part parameters by fitting oriented boxes to the input scan, evaluates an objective function with respect to the continuous part and symmetry parameters ΘB and ΘA, and numerically estimates gradients [amount of change] of the objective function with respect to those parameters. Consistent with the disclosure provided by Applicant’s specification, the numerically estimated gradients constitute the calculated amount or rate of change in the evaluation value relative to the initialized parameter values. )
updating the parameter based on the calculated amount of change in the evaluation value, and
( [Sec. 4.3 > Point segmentation, and Part pose optimization], [Eq. (15)]: "To update the continuous parameters we use an interior point algorithm [Wächter and Biegler 2006] using numerically estimated gradients, optimizing [Eq. 15]": Sung teaches updating the boundary-frame parameters ΘB, ΘA using the numerically estimated gradient computed above. )
identifying a shape of each of the plurality of components when the point-to-part and symmetric point-to-point correspondences do not change.
( [Sec. 4.3 > Point segmentation, and Part pose optimization], [Fig. 4]: Sung re-estimates the point-to-part assignments (M_P), wherein the nodes are points and the labels are assignments of those points to parts (B); alternates between estimating point-to-part, part-to-point, and symmetric point-to-point correspondences and refining the continuous part parameters; and terminates the iterative procedure when the point-to-part and symmetric point-to-point correspondences do not change, thereby producing the final part-structure prediction identifying the component shapes. )
Sung terminates when its point-to-part and symmetric point-to-point correspondences do not change. Sung does not expressly disclose terminating its optimization based on an evaluation-value change satisfying a predetermined range where Besl teaches:
identifying a shape of each of the plurality of components when the calculated amount of change in the evaluation value has converged within a predetermined range.
( [Sec. IV > A. ICP Algorithm Statement > Step (d)]: Besl terminates the iterative shape-registration process when the change in the mean-square-error evaluation value falls below a preset threshold (
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𝜏) specifying the desired registration precision, namely, when (dk - dk+1 <
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𝜏), thereby determining that the evaluation-value change has converged within a predetermined range. )
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Sung’s ICP-inspired part-pose optimization to use Besl’s preset mean-square-error-change threshold as the termination criterion, thereby terminating the optimization when further parameter updates produce insignificant improvement, reducing unnecessary iterations, and identifying the component shapes at a selected precision. Such a modification would have been the predictable use of a known convergence-determination technique according to its established function, with a reasonable expectation of success.
Regarding claim 2, Sung [as modified by Besl] teaches the workpiece measurement method according to claim 1, wherein the condition includes any one of a shape, size, number, and limitation of a boundary frame corresponding to the workpiece.
( [Sec. 3], [Sec. 4.1], [Sec. 4.3]: Sung teaches a boundary-frame (oriented-box) condition that includes a shape/ orientation constraint (the orthogonality constraint C(ΘB) on rotation Rb), a size parameter with learned priors on relative scale (the anisotropic scaling sb, constrained via the pairwise part-relation energy Epair), a number of boundary frames per category (the recorded permutations of part configurations), and a limitation/ connection relationship between boundary frames (the part-symmetry constraint C(ΘA,ΘB) of Eq. 11 enforcing that part-to-part symmetries are preserved at the box scale), each defined in correspondence with the trained shape category serving as the measurement target. )
Regarding claim 3, Sung [as modified by Besl] teaches the workpiece measurement method according to claim 1, wherein the evaluation function is a weighted linear sum according to the number of points in a point cloud included in the boundary frame and a point cloud density.
( [Sec. 4.2], [Eq. (1), (3)-(5), & (12)]: Sung represents each component by an oriented box fitted around the scan points assigned to the component and defines the final evaluation energy as a weighted linear sum, E = w₁Eₚₙₜ + w₂Eₛₘₒₒₜₕ + w₃Eₛₘᴅ + w₄Eₚₐᵢᵣ + w₅Eₛᵧₘₘ. The point-classification term Eₚₙₜ and the point-to-box term Eₚ→Q are normalized using nᵦ = |{p ∈ P | m(p) = b}|, which Sung identifies as the number of scan points assigned to part b. The box-to-point term E_Q→P is evaluated using sample points Q distributed over the oriented-box surface at a spatially uniform sampling density and measures the proximity of those sampled locations to the assigned point cloud. )
Regarding claim 4, Sung [as modified by Besl] teaches the workpiece measurement method according to claim 1, wherein the optimizing step includes optimizing the parameter including any one of a size, position, and angle of the boundary frame.
( [Sec. 4.1], [Sec. 4.3], [Eq. (15)]: Sung represents each part by an oriented box parameterized by a three-dimensional rotation (Rb), translation (tb), and anisotropic scale (sb), corresponding respectively to the angle, position, and size of the box, and refines these continuous part-pose parameters during optimization. )
Regarding claim 8, Sung [as modified by Besl] teaches the workpiece measurement method according to claim 1, wherein the boundary frame includes a straight line or a curved line.
( [Sec. 4.1], [Fig. 2]: Sung depicts and represents each component using an oriented box whose straight edges define the boundary of the corresponding part, thereby teaching a boundary frame that includes straight lines. )
Regarding claim 9, Sung [as modified by Besl] teaches the workpiece measurement method according to claim 1, wherein the boundary frame is indicated two-dimensionally or three-dimensionally.
( [Sec. 4.1], [Fig. 2]: Sung represents each component using a three-dimensional oriented box formed from a unit cube that is scaled, rotated, and translated in three-dimensional space according to (sb), (Rb), and (tb), thereby teaching a boundary frame indicated three-dimensionally. )
Regarding claims 11-12, the rationale provided in the rejection of claim 1 is incorporated herein. Further, the method of claim 1 corresponds to the system of claim 11, as well as the computer readable medium of claim 12 ( [Sung, Sec. 6 > “Analyzing Kinect Scans” and “Timing”]: Sung processes 3D scan data obtained using a Kinect 2 and implements the disclosed algorithm as a single-threaded CPU-only C++ program executed on a 2.6 GHz Intel processor. ), and performs the steps disclosed herein.
Claims 5-7 and 10 are rejected under 35 U.S.C. §103 as being unpatentable over Sung [as modified by Besl] in view of Huebner (Huebner et al, “Minimum Volume Bounding Box Decomposition for Shape Approximation in Robot Grasping”, 2008).
Regarding claim 5, Sung [as modified by Besl] teaches the workpiece measurement method according to claim 1,
Sung [as modified by Besl] teaches acquiring and segmenting 3D point-cloud data and estimating and optimizing oriented boundary boxes for the component parts, but fails to expressly disclose whereas Huebner teaches:
wherein the outline estimating step includes estimating the boundary frame by scanning the point cloud data from a plurality of directions.
( [Sec. III-C > "Computing the Best Split"], [Sec. III.D], [Figs. 2–4], [Eq. (1)]: Huebner projects the point-cloud data onto two-dimensional grids corresponding to three faces of a parent minimum-volume bounding box, evaluates grid splits along six directions (two directions for each face) and selects the best directional split. Huebner then divides the point cloud into corresponding subsets and fits child minimum-volume bounding boxes to the subsets, thereby estimating boundary frames by scanning the point-cloud data from a plurality of directions. )
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Sung [as modified by Besl] to use Huebner’s six-direction projected-grid search when estimating component boxes, thereby locating component boundaries efficiently and producing tighter-fitting boundary frames. Such a modification would have been the predictable use of a known multidirectional box-estimation technique according to its established function, with a reasonable expectation of success.
Regarding claim 6, Sung [as modified by Besl] teaches the workpiece measurement method according to claim 1,
Sung [as modified by Besl] teaches acquiring and segmenting 3D point-cloud data and estimating and optimizing oriented boundary boxes for the component parts, but fails to expressly disclose whereas Huebner teaches:
wherein the outline estimating step includes estimating an outline by projecting the point cloud data onto a two-dimensional plane.
( [Sec. III-C > "Computing the Best Split"], [Sec. III.D], [Figs. 2–4], [Eq. (1)]: Huebner projects the three-dimensional point-cloud data onto two-dimensional grids corresponding to the three faces of a parent minimum-volume bounding box. Huebner evaluates the projected point-cloud outlines using two-dimensional rectangular bounds and directional grid splits, selects the best split, and fits child minimum-volume bounding boxes to the resulting point subsets, thereby estimating component outlines from two-dimensional projections of the point-cloud data. )
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Sung [as modified by Besl] to use Huebner’s two-dimensional face projections when estimating component boxes, thereby simplifying the three-dimensional boundary search and efficiently producing tighter-fitting boundary frames. Such a modification would have been the predictable use of a known projection-based outline-estimation technique according to its established function, with a reasonable expectation of success.
Regarding claim 7, Sung [as modified by Besl and Huebner] teaches the workpiece measurement method according to claim 6, further comprising a deriving step for deriving a position corresponding to each of the plurality of components in an axial direction orthogonal to the two-dimensional plane.
( [Secs. III-A, III-C, and III-D], [Fig. 3]: Huebner projects the point-cloud data onto two-dimensional grids corresponding to the faces of the parent box, divides the original three-dimensional point cloud into component subsets according to the selected projected split, and computes a tight-fitting three-dimensional child minimum-volume bounding box for each subset. The three-dimensional position of each resulting child box necessarily includes its position along the axis normal, and therefore orthogonal, to the corresponding two-dimensional projection plane. )
Claim 10 is rejected under 35 U.S.C. §103 as being unpatentable over Sung [as modified by Besl] in view of Wang (Wang et al, “3D Shape Perception from Monocular Vision, Touch, and Shape Priors”, 2018).
Regarding claim 10, Sung [as modified by Besl] teaches the workpiece measurement method according to claim 1,
Sung [as modified by Besl] fails to expressly disclose where Wang teaches:
further comprising a correcting step for correcting the at least one boundary frame optimized in the optimizing step by using a measurement result obtained by performing touch-sensing on the workpiece.
( Wang > Section III.B > para 1: tactile sensing on an object using a GelSight sensor is used to refine a 3D shape predicted using image data alone. )
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify Sung [as modified by Besl] using Wang’s teachings by incorporating using tactile sensing to correct the optimized boundary frame of Sung [as modified by Besl], in order to refine image-based predictions using accurate touch-based data especially in cases of uncertainty or occlusions (see Abstract and Section I > para 5).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEN KUDO whose telephone number is (571)272-4498. The examiner can normally be reached M-F 8am - 5pm.
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KEN KUDO
Examiner
Art Unit 2671
/KEN KUDO/Examiner, Art Unit 2671
/VINCENT RUDOLPH/Supervisory Patent Examiner, Art Unit 2671
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