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 .
Priority
Examiner acknowledges that this application is a continuation of US application 17/315,741 filed on 05/10/2021 and claims earliest priority from the US provisional application 63/023,089 filed on 05/11/2020.
Information Disclosure Statement
The information disclosure statements (“IDS”) filed on 01/17/2025, 04/04/2025, 06/30/2025 and 03/20/2026 has been reviewed and the listed references have been considered.
Drawings
The 11-page drawings have been considered and placed on record in the file.
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, 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-6, 8-10, 17 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Wagner et al. (US 2014/0267397 A1) in view of Roumeliotis et al. (US 2019/0154449 A1).
Regarding claim 1, Wagner teaches, A computing system configured to (Wagner, ¶0026: “an in-situ target creation module (ITC) as described herein may initialize”) generate a representation (Wagner, ¶0046: “The ITC can output an AR representation associated with the processed images”) of an environment, (Wagner, ¶0002: “images can be used as input to build a 3D map of an environment”) the computing system comprising: one or more processors; (Wagner, ¶0012: “a data processing system including a processor”) and at least one computer readable medium comprising computer executable instructions that, when executed (Wagner, ¶0012: “a storage device configurable to store instructions to perform”) by at least one processor of the one or more processors: (Wagner, ¶0012: “The instructions cause the processor to initialize”) obtain sensor captured information, (Wagner, ¶0002: “AR system can include input from a camera sensor”) the sensor captured information comprising a plurality of images; (Wagner, ¶0002: “input from a camera sensor to record real world objects as images”) provide an initial representation of the environment, (Wagner, ¶0002: “images can be used as input to build a 3D map of an environment”) (Wagner, ¶0028: “initialize the planar target by treating (e.g., passing a viewpoint parameter/configuration during initialization) the entire captured camera image”) the initial parameters of the M planar features indicating normals of planes represented by the M planar features; (Wagner, ¶0050: “ITC can accurately triangulate the target features to calculate the area covered by the planar target in the first and second reference images and the planar target's true plane normal in the first and second reference images”) and compute N refined poses and refined parameters of the M planar features by jointly adjusting the N initial poses and the initial parameters of the M planar features. (Wagner, ¶0067: “bundle adjustment can be defined as simultaneously refining the 3D coordinates describing scene geometry as well as the parameters of the relative motion and optical characteristics of the camera”). Although Wagner computes a single initial pose of the camera ¶0063: “a first camera pose of the first reference image”, however, Wagner does not explicitly teach multiple initial camera poses, the initial representation comprising N initial poses.
In an analogous field of endeavor, Roumeliotis teaches the initial representation comprising N initial poses. (Roumeliotis, ¶0023: “vision system having multiple cameras to produce 3D information”; ¶0005: “geometrically relate the multiple poses from which the respective feature was observed”).
Therefore, 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 Wagner using the teachings of Roumeliotis to introduce obtaining camera information from multiple poses. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of producing a more accurate 3D representation of the environment. Therefore, it would have been obvious to combine the analogous arts Wagner and Roumeliotis to obtain the invention in claim 1.
Regarding claim 2, Wagner in view of Roumeliotis teaches, The computing system of claim 1, wherein: the one or more processors comprise a processor of a wearable or portable device. (Wagner, ¶0055: “device 100 can be a portable electronic device (e.g., smart phone, dedicated augmented reality (AR) device, game device, wearable device such as eyeglasses, or other device with AR processing and display capabilities”).
Regarding claim 3, Wagner in view of Roumeliotis teaches, The computing system of claim 1, comprising: a removable power source configured to provide power to the one or more processors. (Wagner, ¶0024: “Device 100 may include various other elements, such as a satellite position system receiver, power device (e.g., a battery), as well as other components typically associated with portable and non-portable electronic devices”).
Regarding claim 4, Wagner in view of Roumeliotis teaches, The computing system of claim 2, wherein the at least one computer readable medium comprising computer executable instructions that, when executed by at least one processor of the one or more processors: (Wagner, ¶0012: “The instructions further cause the processor to process one or more subsequent images”) for each of the M planar features at each pose corresponding to an image of the plurality of images comprising one or more observations of the planar feature, (Wagner, ¶0012: “select a second reference image from the processed one or more subsequent images, and track the planar target in 6DoF, and refine the planar target to a more accurate planar target”) compute a matrix indicating the one or more observations of the planar feature, (Wagner, ¶0053: “position and orientation (pose) can be described by means of a rotation and translation transformation, which brings the object from a reference pose to the observed pose. This rotation transformation can be represented in different ways (e.g., as a rotation matrix”) and factorize the matrix into (Roumeliotis, ¶0061: “apply the following thin QR factorization”; Applicant’s specification ¶0136: “The thin QR decomposition may be used”) two or more matrices, the two or more matrices comprising one matrix having reduced rows compared with the matrix. (Roumeliotis, ¶0065: “Accordingly, U.sub.1′ and U.sub.2′ are orthogonal to one another (e.g., U.sub.1′.sup.T U.sub.2′=0) and the resulting U′.sup.TL′.sub.k+1.sup.⊕.sup.−1 is block upper-triangular”).
Therefore, 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 Wagner in view of Roumeliotis using the additional teachings of Roumeliotis to introduce thin QR factorization. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of reducing the computational complexity to improve the performance. Therefore, it would have been obvious to combine the analogous arts Wagner and Roumeliotis to obtain the invention in claim 4.
Regarding claim 5, Wagner in view of Roumeliotis teaches, The computing system of claim 4, wherein: the N refined poses and the refined parameters of the M planar features is computed based at least in part on the matrices having reduced rows. (Roumeliotis, ¶0031: “a matrix that contains estimates of the uncertainty of each predicted state estimate in state vector”; and ¶0043: “estimator 22 maintains a state vector x comprising poses and other variables of interest”).
Therefore, 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 Wagner in view of Roumeliotis using the additional teachings of Roumeliotis to introduce encoding pose and feature information in a matrix. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of efficiently processing the feature and pose information. Therefore, it would have been obvious to combine the analogous arts Wagner and Roumeliotis to obtain the invention in claim 5.
Regarding claim 6, Wagner in view of Roumeliotis teaches, The computing system of claim 4, wherein: for each of the M planar features at each pose corresponding to an image of the plurality of images comprising one or more observations of the planar feature, (Wagner, ¶0053: “position and orientation (pose) can be described by means of a rotation and translation transformation, which brings the object from a reference pose to the observed pose”) factorizing the matrix into two or more matrices comprises computing an orthogonal matrix and an upper triangular matrix; (Roumeliotis, ¶0065: “Accordingly, U.sub.1′ and U.sub.2′ are orthogonal to one another (e.g., U.sub.1′.sup.T U.sub.2′=0) and the resulting U′.sup.TL′.sub.k+1.sup.⊕.sup.−1 is block upper-triangular”) the N refined poses and the refined parameters of the M planar features is computed based at least in part on the upper triangular matrices. (Roumeliotis, ¶0063: “estimator 22 determines a square orthonormal matrix U, with U.sup.TU=UU.sup.T=I, such that U.sup.TL′k+1.sup.⊕.sup.−1 has a block upper-triangular structure”).
Therefore, 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 Wagner in view of Roumeliotis using the additional teachings of Roumeliotis to introduce an upper triangular matrix. A person skilled in the art would be motivated to combine the known elements as described above and achieve high computational efficiency. Therefore, it would have been obvious to combine the analogous arts Wagner and Roumeliotis to obtain the invention in claim 6.
Regarding claim 8, Wagner in view of Roumeliotis teaches, The computing system of claim 1, wherein: the representation of the environment comprises the N refined poses and the refined parameters of the M planar features. (Wagner, ¶0057: “when the camera 114 moves and camera pose changes… features from the second reference image may be extracted and triangulated with features from the first image frame to refine the target and increase tracking accuracy”; Applicant’s specification ¶0151: “As the features are observed by subsequent images, the initial predictions may be refined to reduce drift and improve the quality of the presentation”).
Regarding claim 9, it recites a method with steps corresponding to the elements of system recited in claim 1. Therefore, the recited steps of method claim 9 are mapped to the proposed combination in the same manner as the corresponding elements in system claim 1. Additionally, the rationale and motivation to combine Wagner and Roumeliotis presented in rejection of claim 1, apply to this claim. In addition, Wagner further teaches, A method (Wagner, ¶0009: “a method for planar target creation and tracking”).
Regarding claim 10, Wagner in view of Roumeliotis teaches, The method of claim 9, wherein: the sensor captured information is captured by sensors of a wearable or portable device. (Wagner, ¶0055: “device 100 can be a portable electronic device (e.g., smart phone, dedicated augmented reality (AR) device, game device, wearable device such as eyeglasses, or other device with AR processing and display capabilities”).
Regarding claim 17, Wagner in view of Roumeliotis teaches, The method of claim 9, wherein: the representation of the environment comprises the N refined poses and the refined parameters of the M planar features. (Wagner, ¶0057: “when the camera 114 moves and camera pose changes… features from the second reference image may be extracted and triangulated with features from the first image frame to refine the target and increase tracking accuracy”; Applicant’s specification ¶0151: “As the features are observed by subsequent images, the initial predictions may be refined to reduce drift and improve the quality of the presentation”).
Regarding claim 18, it recites a non-transitory computer-readable medium storing computer executable instructions corresponding to the elements of the system recited in claim 1. Therefore, the recited instructions of the computer-readable medium of claim 18 are mapped to the proposed combination in the same manner as the corresponding elements of the system claim 1. Additionally, the rationale and motivation to combine Wagner and Roumeliotis presented in rejection of claim 1, apply to this claim. In addition, Wagner further teaches, A non-transitory computer-readable medium storing computer executable instructions configured to, (Wagner, ¶0010: “a computer readable non-transitory storage medium with instructions to perform”) when executed by at least one processor, (Wagner, ¶0076: “in a software module executed by a processor”) perform a method for operating a computing system to generate a representation of an environment (Wagner, ¶0033: “cause the device display to output an augmented reality representation of the target immediately, in real-time, near real-time, or within a short time window of the initialization of the planar target”).
Claims 7, 11-14, 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Wagner et al. (US 2014/0267397 A1) in view of Roumeliotis et al. (US 2019/0154449 A1) and in further view of Nakae et al. (US 2022/0207425 A1).
Regarding claim 7, Wagner in view of Roumeliotis teaches, The computing system of claim 4, wherein for each of the M planar features at each pose corresponding to an image of the plurality of images comprising one or more observations of the planar feature, (Wagner, ¶0053: “position and orientation (pose) can be described by means of a rotation and translation transformation, which brings the object from a reference pose to the observed pose”). However, Wagner and Roumeliotis does not explicitly teach, the matrix indicating the one or more observations of the planar feature is computed by: for each of the one or more observations of the planar feature, computing a matrix block indicating said observation; and stacking the matrix blocks into the matrix indicating the one or more observations of the planar feature.
In an analogous field of endeavor, Nakae teaches, the matrix indicating the one or more observations of the planar feature is computed by: (Nakae, ¶0243: “The first processing means 121 can derive a covariance matrix from this n×d matrix”) for each of the one or more observations of the planar feature, (Nakae, ¶0243: “the covariance matrix derived from the first processing means 121, variance of each feature is retained”) computing a matrix block indicating said observation; and stacking the matrix blocks into the matrix indicating the one or more observations of the planar feature. (Nakae, ¶0243: “express the plurality of supervisory data with an n×d matrix when the number of the supervisory data (number of samples) obtained by the obtaining means 110 is set as n and the number of features comprised in each supervisory data is set as d”).
Therefore, 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 Wagner in view of Roumeliotis using the teachings of Nakae to introduce stacking observed feature data. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of generating a feature matrix to represent the observed features from the obtained images. Therefore, it would have been obvious to combine the analogous arts Wagner, Roumeliotis and Nakae to obtain the invention in claim 7.
Regarding claim 11, Wagner in view of Roumeliotis teaches, The method of claim 10 for each of the M planar features at each pose corresponding to an image of the plurality of images comprising one or more observations of the planar feature, (Wagner, ¶0053: “position and orientation (pose) can be described by means of a rotation and translation transformation, which brings the object from a reference pose to the observed pose”). However, Wagner in view of Roumeliotis does not explicitly teach, computing a matrix having P rows, P being less than a number of the one or more observations of the planar feature, wherein: computing the N refined poses and the refined parameters of the M planar features is based at least in part on the matrices having P rows.
In an analogous field of endeavor, Nakae teaches, computing a matrix having P rows, P being less than a number of the one or more observations of the planar feature, wherein: computing the N refined poses and the refined parameters of the M planar features is based at least in part on the matrices having P rows. (Nakae, ¶0243: “the first processing means 121 can express the plurality of supervisory data with an n×d matrix when the number of the supervisory data (number of samples) obtained by the obtaining means 110 is set as n and the number of features comprised in each supervisory data is set as d. The first processing means 121 can derive a covariance matrix from this n×d matrix”).
Therefore, 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 Wagner using the teachings of Nakae to introduce stacking observed feature data in a matrix. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of generating a feature matrix to efficient processing of image information. Therefore, it would have been obvious to combine the analogous arts Wagner, Roumeliotis and Nakae to obtain the invention in claim 11.
Regarding claim 12, Wagner in view of Roumeliotis and in further view of Nakae teaches, The method of claim 11, wherein for each of the M planar features at each pose corresponding to an image of the plurality of images comprising one or more observations of the planar feature, computing the matrix having P rows comprises: (Nakae, ¶0243: “The first processing means 121 can derive a covariance matrix from this n×d matrix”) computing a matrix indicating the one or more observations of the planar feature; (Nakae, ¶0243: “the covariance matrix derived from the first processing means 121, variance of each feature is retained”) and factorizing the matrix into two or more matrices, the two or more matrices comprising the matrix having P rows. (Nakae, ¶0251: “decomposing a matrix into an orthogonal matrix and an upper triangular matrix”).
Therefore, 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 Wagner in view of Roumeliotis and in further view of Nakae using the additional teachings of Nakae to introduce matrix decomposition. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of efficiently processing of feature data represented by the decomposed matrices. Therefore, it would have been obvious to combine the analogous arts Wagner, Roumeliotis and Nakae to obtain the invention in claim 12.
Regarding claim 13, Wagner in view of Roumeliotis and in further view of Nakae teaches, The method of claim 12, wherein: factorizing the matrix into two or more matrices comprises computing an orthogonal matrix and an upper triangular matrix; (Nakae, ¶0251: “decomposing a matrix into an orthogonal matrix and an upper triangular matrix”) and computing the N refined poses and the refined parameters of the M planar features is based at least in part on the upper triangular matrices. (Nakae, ¶0283: “the processor 120 adds a mean value to each feature of the upper triangular matrix to which a random number has been applied in step S405. This enables recovery of information”).
Therefore, 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 Wagner in view of Roumeliotis and in further view of Nakae using the additional teachings of Nakae to introduce matrix decomposition into orthogonal and upper triangular matrices. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of efficiently processing feature data represented in the decomposed matrices. Therefore, it would have been obvious to combine the analogous arts Wagner, Roumeliotis and Nakae to obtain the invention in claim 13.
Regarding claim 14, Wagner in view of Roumeliotis and in further view of Nakae teaches, The method of claim 12, wherein for each of the M planar features at each pose corresponding to an image of the plurality of images comprising one or more observations of the planar feature, computing the matrix indicating the one or more observations of the planar feature (Wagner, ¶0053: “position and orientation (pose) can be described by means of a rotation and translation transformation, which brings the object from a reference pose to the observed pose. This rotation transformation can be represented in different ways (e.g., as a rotation matrix”) comprises: for each of the one or more observations of the planar feature, computing a matrix block indicating said observation; (Nakae, ¶0243: “The first processing means 121 can derive a covariance matrix from this n×d matrix”) and stacking the matrix blocks into the matrix indicating the one or more observations of the planar feature. (Nakae, ¶0243: “the first processing means 121 can express the plurality of supervisory data with an n×d matrix when the number of the supervisory data (number of samples) obtained by the obtaining means 110 is set as n and the number of features comprised in each supervisory data is set as d”).
Therefore, 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 Wagner in view of Roumeliotis and in further view of Nakae using the additional teachings of Nakae to introduce stacking observed feature data. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of generating a feature matrix to represent the observed features from the obtained images. Therefore, it would have been obvious to combine the analogous arts Wagner, Roumeliotis and Nakae to obtain the invention in claim 14.
Regarding claim 19, Wagner in view of Roumeliotis teaches, The non-transitory computer-readable medium of claim 18, wherein: the method comprises, for each of the M planar features at each pose corresponding to an image of the plurality of images comprising one or more observations of the planar feature, (Wagner, ¶0012: “select a second reference image from the processed one or more subsequent images, and track the planar target in 6DoF, and refine the planar target to a more accurate planar target”). However, the combination of Wagner and Roumeliotis does not explicitly teach, computing a matrix having P rows, P being less than a number of the one or more observations of the planar feature; computing the N refined poses and the refined parameters of the M planar features is based at least in part on the matrices having P rows; and the representation of the environment comprises the N refined poses and the refined parameters of the M planar features.
In an analogous field of endeavor, Nakae teaches, computing a matrix having P rows, P being less than a number of the one or more observations of the planar feature; computing the N refined poses and the refined parameters of the M planar features is based at least in part on the matrices having P rows; and the representation of the environment comprises the N refined poses and the refined parameters of the M planar features. (Nakae, ¶0243: “the first processing means 121 can express the plurality of supervisory data with an n×d matrix when the number of the supervisory data (number of samples) obtained by the obtaining means 110 is set as n and the number of features comprised in each supervisory data is set as d. The first processing means 121 can derive a covariance matrix from this n×d matrix”).
Therefore, 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 Wagner in view of Roumeliotis using the teachings of Nakae to introduce stacking observed feature data. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of generating a feature matrix to represent each of the observed features from the obtained images. Therefore, it would have been obvious to combine the analogous arts Wagner, Roumeliotis and Nakae to obtain the invention in claim 19.
Regarding claim 20, Wagner in view of Roumeliotis and in further view of Nakae teaches, The non-transitory computer-readable medium of claim 19, wherein for each of the M planar features at each pose corresponding to an image of the plurality of images comprising one or more observations of the planar feature, computing the matrix having P rows comprises: (Nakae, ¶0243: “The first processing means 121 can derive a covariance matrix from this n×d matrix”) computing a matrix indicating the one or more observations of the planar feature; (Nakae, ¶0243: “the covariance matrix derived from the first processing means 121, variance of each feature is retained”) and factorizing the matrix into two or more matrices, the two or more matrices comprising the matrix having P rows. (Nakae, ¶0251: “decomposing a matrix into an orthogonal matrix and an upper triangular matrix”).
Therefore, 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 Wagner in view of Roumeliotis and in further view of Nakae using the additional teachings of Nakae to introduce matrix decomposition. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of efficiently processing of feature data represented by the decomposed matrices. Therefore, it would have been obvious to combine the analogous arts Wagner, Roumeliotis and Nakae to obtain the invention in claim 20.
Claims 15 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Wagner et al. (US 2014/0267397 A1) in view of Roumeliotis et al. (US 2019/0154449 A1) in further view of Nakae et al. (US 2022/0207425 A1) and still in further view of Alismail (Direct Pose Estimation and Refinement - disclosed in the IDS dated 01/17/2025).
Regarding claim 15, Wagner in view of Roumeliotis and in further view of Nakae teaches, The method of claim 11, wherein computing the N refined poses and the refined parameters of the M planar features comprises. However, the combination of Wagner, Roumeliotis and Nakae does not explicitly teach, computing reduced Jacobian matrix blocks based at least in part on the matrices P rows; stacking the reduced Jacobian matrix blocks to form a reduced Jacobian matrix; and providing the reduced Jacobian matrix to an algorithm that solves least-squares problem to update current estimate of the N refined poses and the refined parameters of the M planar features.
Alismail teaches, computing reduced Jacobian matrix blocks based at least in part on the matrices P rows; (Alismail, page 53, ¶0005: "accurate approximation of the Jacobian (and Hessian) of the cost function") stacking the reduced Jacobian matrix blocks to form a reduced Jacobian matrix; (Alismail, page 81, ¶0001: "Letting JE R nx6 be the Jacobian of the objective, obtained by stacking the partial derivatives of the image") and providing the reduced Jacobian matrix to an algorithm that solves least-squares problem (Alismail, page 30, ¶0001: "algorithms to solving least-squares problem: Gauss-Newton and Levenberg-Marquardt") to update current estimate of the N refined poses and the refined parameters of the M planar features. (Alismail, page 86, ¶0002: "Least-Squares (IRLS) optimization using an M-Estimator framework" and page 63, ¶0005: "estimate is updated").
Therefore, 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 Wagner in view of Roumeliotis and in further view of Nakae using the teachings of Alismail to introduce algorithms that solve least-square problems. A person skilled in the art would be motivated to combine the known elements, as described above, and achieve the predictable result of higher efficiency in matrix computation. Therefore, it would have been obvious to combine the analogous arts Wagner, Roumeliotis, Nakae and Alismail to obtain the invention in claim 15.
Regarding claim 16, Wagner in view of Roumeliotis and in further view of Nakae teaches, The method of claim 11, wherein computing the N refined poses and the refined parameters of the M planar features comprises. However, the combination of Wagner, Roumeliotis and Nakae does not explicitly teach, computing reduced residual blocks based at least in part on the matrices having P rows; stacking the reduced residual blocks to form a reduced residual vector; and providing the reduced residual vector to an algorithm that solves least-squares problem to update current estimate of the N refined poses and the refined parameters of the M planar features.
In an analogous field of endeavor, Alismail teaches, computing reduced residual blocks based at least in part on the matrices having P rows; (Alismail, page 64, ¶0005: "a list of residuals r = (r1, , rm)T") stacking the reduced residual blocks (Alismail, page 27, ¶0001: "stacking the residuals in a vector r") to form a reduced residual vector; (Alismail, page 76, ¶0006: "compute the vector of residuals") and providing the reduced residual vector to an algorithm that solves least-squares problem (Alismail, page 30, ¶0001: "algorithms to solving least-squares problem: Gauss-Newton and Levenberg-Marquardt") to update current estimate of the N refined poses and the refined parameters of the M planar features. (Alismail, page 86, ¶0002: "Least-Squares (IRLS) optimization using an M-Estimator framework" and page 63, ¶0005: "estimate is updated").
Therefore, 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 Wagner in view of Roumeliotis and in further view of Nakae using the teachings of Alismail to introduce computing a vector of residuals. A person skilled in the art would be motivated to combine the known elements, as described above, and achieve the predictable result of increasing the efficiency and accuracy of the matrix-based feature processing. Therefore, it would have been obvious to combine the analogous arts Wagner, Roumeliotis, Nakae and Alismail to obtain the invention in claim 16.
Conclusion
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/MEHRAZUL ISLAM/Examiner, Art Unit 2662
/AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
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