CTNF 18/872,862 CTNF 90210 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. DETAILED ACTION Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 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. 07-07-aia AIA 07-07 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention. 07-12-aia AIA (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 07-15-03-aia AIA Claim 1-3, 5, 7-11, 13, 15-16 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Lachinski et al. (US Patent 12,566,899 B2) . As to claim 1 , Lachinski discloses a method comprising: obtaining a three-dimensional (3D) model of a 3D scene and localization data (Claim 1, “receiving periodic new spatially accurate geometric information for human-made managed structures” “three-dimensional (3D) geometric plane creation drawing tools are used to derive or update 3D model mathematical objects from the new spatially accurate geometric information”); localizing a scanning device in the 3D scene according to the localization data and the 3D model (Claim 1, “retrieving most recent versions of all existing 4D property models and 4D structure models of the managed structures””determining current revision status of all current 3D structure models of the managed structures for the managed area” Fig. 18, Col 15, lines 1-43, “Structure Sensor 1708 (FIG. 19 ) by Occipital, Inc. located in San Francisco, CA which is an addon to the iPAD that allows for complete 3D scanning of building interiors. Specifically, the addon is a mobile 3D sensor that gives the iPad the ability to perceive depth and “see in 3D.” It combines that data with the iPad's color camera and IMU to create a 3D model. Leica Geosystems markets a product called Disto 1710 (FIG. 19) which makes measurements between two points using a laser beam.”); scanning the 3D scene with the scanning device and detecting differences between the 3D model and the scanned 3D scene ( Fig. 18, Col 15, lines 1-43, “allows for complete 3D scanning of building interiors” claim 1, “retrieving most recent versions of all existing 4D property models and 4D structure models of the managed structures” “determining current revision status of all current 3D structure models of the managed structures for the managed area” “each 3D structure model is overlaid on the new spatially accurate geometric information to confirm a revision status for the 3D structure model,”) ; highlighting the differences in a view of the 3D scene (Claim 1, “each 3D structure model is overlaid on the new spatially accurate geometric information to confirm a revision status for the 3D structure model,” Col 16, lines 43-51, “To provide change management for man-made structures, periodic aerial oblique imagery supplemented by available LiDAR (or equivalent active measurements) is needed to automatically create the geometry for the made-made structures. Even with maximum automation of man-made structures, a perspective view editor is still needed to overlay existing sketch records against the imagery and LiDAR to check the accuracy of the sketch and to make any modifications that may be required.”); and modifying the 3D model according to a change detection mode (Claim 1, “wherein each 3D structure model has one and only one revision status at any given time” “storing new 3D structure models with a capture date of the new spatially accurate geometric information, its attributes, revision status, and a unique identifier; wherein the revision status for each 3D structure model for each of the managed structures in the managed area becomes available to the community of users” Col 23, lines 45-66, Col 24, lines 1-58, “subsequent editing with the 3D perspective sketching module.” “editing real world objects shown in natural image and/or 3D point clouds and/or Digital Surface models”). As to claim 2 , claim 1 is incorporated and Lachinski discloses a user is able to modify the change detection mode between a scanning of two parts of the 3D scene, and wherein the change detection mode belongs to a set of modes comprising: keep detected removals and add detected insertions; remove detected removals and ignore detected insertions; keep detected removals and ignore detected insertions; and remove detected removals and add detected insertions (Col 15, lines 44-53, “While users are conducting their assigned job tasks, they may also use productivity tools 1607 such as but not limited to; 3D map layers, create map layers using attribute data as criteria and view orthogonal or oblique imagery with map layers overlaid upon them. As the user completes and saves his or her work, each save triggers a synchronization process where the mobile application software pushes all new edits to all data types since the last synchronization.“ Claim 1, “the revision status of each 3D structure model is selected from the following group: unchanged, when correct; modified, when changed to be correct; added, when missing; and deleted, when the 3D structure model is no longer relevant;”). As to claim 3 , claim 2 is incorporated and Lachinski discloses the set of change detection modes comprises a manual mode in which one or more change detection options are displayed to a user, wherein the one or more change detection options comprise one or more of keeping detected removals, ignoring detected removals, keeping detected insertions, and ignoring detected insertions, and wherein the 3D model is modified upon a choice of at least one of the one or more change detection options by the user (Col 18, lines 48-57, “The user may dynamically set the viewer location and perspective view when the camera view is not needed to create or edit a 3D model. Existing 3D point clouds, 3D model templates and existing drawings may be inserted into the scene for editing. The user may also select an ortho mode which permits the user to use a camera view model that emulates viewing and accurate editing in 3D orthographic imagery. This is accomplished by setting the viewer location directly above or below the structure location at a distance sufficient to provide accurate results.” Claim 1, “the revision status of each 3D structure model is selected from the following group: unchanged, when correct; modified, when changed to be correct; added, when missing; and deleted, when the 3D structure model is no longer relevant;”). As to claim 5 , claim 1 is incorporated and Lachinski discloses the scanning device captures RGB(D) frames of a part of the 3D scene, the differences are detected by comparing the RGB(D) frames with a corresponding part of the 3D model (Col 15, lines 10-20, “The invention supports full integration of products such as Structure Sensor 1708 (FIG. 19 ) by Occipital, Inc. located in San Francisco, CA which is an addon to the iPAD that allows for complete 3D scanning of building interiors. Specifically, the addon is a mobile 3D sensor that gives the iPad the ability to perceive depth and “see in 3D.” It combines that data with the iPad's color camera and IMU to create a 3D model. Leica Geosystems markets a product called Disto 1710 (FIG. 19 ) which makes measurements between two points using a laser beam.”. Claim 1, “each 3D structure model is overlaid on the new spatially accurate geometric information to confirm a revision status for the 3D structure model,” Col 16, lines 43-51, “To provide change management for man-made structures, periodic aerial oblique imagery supplemented by available LiDAR (or equivalent active measurements) is needed to automatically create the geometry for the made-made structures. Even with maximum automation of man-made structures, a perspective view editor is still needed to overlay existing sketch records against the imagery and LiDAR to check the accuracy of the sketch and to make any modifications that may be required.”). As to claim 7 , claim 1 is incorporated and Lachinski discloses the 3D model is a 3D mesh and wherein modifying the 3D model comprises modifying faces of the 3D mesh (Col 23, lines 45-66, Col 24, lines 1-58, “A Digital Surface Model (DSM) is defined here as a 3D regular grid or triangulated mesh.” “By analyzing color variations, facet slope, and distance above ground, 3D facets are automatically generated and categorized for comparison with the existing 3D model or subsequent editing with the 3D perspective sketching module.” A facet is a specific, specialized type of face.). As to claim 8 , claim 1 is incorporated and Lachinski discloses the highlighting of the differences is performed over a period of time after the detection of the differences ( Col 16, lines 43-51, “To provide change management for man-made structures, periodic aerial oblique imagery supplemented by available LiDAR (or equivalent active measurements) is needed to automatically create the geometry for the made-made structures. Even with maximum automation of man-made structures, a perspective view editor is still needed to overlay existing sketch records against the imagery and LiDAR to check the accuracy of the sketch and to make any modifications that may be required.”) . As to claim 9 , Lachinski discloses a device comprising a scanning device and a display device and configured for: obtaining a three-dimensional (3D) model of a 3D scene and localization data; localizing a scanning device in the 3D scene according to the localization data and the 3D model; scanning the 3D scene with the scanning device and detecting differences between the 3D model and the scanned 3D scene; highlighting the differences in a view of the 3D scene displayed on the display device; and modifying the 3D model according to a change detection mode (See claim 1 for detailed analysis.). As to claim 10 , claim 9 is incorporated and Lachinski discloses a user is able to modify the change detection mode between a scanning of two parts of the 3D scene, and wherein the change detection mode belongs to a set of modes comprising: keep detected removals and add detected insertions; remove detected removals and ignore detected insertions; keep detected removals and ignore detected insertions; and remove detected removals/add detected insertions (See claim 2 for detailed analysis.). As to claim 11 , claim 10 is incorporated and Lachinski discloses the set of change detection modes comprises a manual mode in which one or more change detection options are displayed to a user, wherein the one or more change detection options comprise one or more of keeping detected removals, ignoring detected removals, keeping detected insertions, and ignoring detected insertions, and wherein the 3D model is modified upon a choice of an at least one of the one or more change detection options by the user (See claim 3 for detailed analysis.). As to claim 13 , claim 9 is incorporated and Lachinski discloses the scanning device captures RGB(D) frames of a part of the 3D scene, the differences are detected by comparing the RGB(D) frames with a corresponding part of the 3D model (See claim 5 for detailed analysis.). As to claim 15 , claim 9 is incorporated and Lachinski discloses the 3D model is a 3D mesh and wherein modifying the 3D model is modifying faces of the 3D mesh (See claim 7 for detailed analysis.). As to claim 16 , claim 9 is incorporated and Lachinski discloses the highlighting of the differences is performed over a period of time after the detection of the differences (See claim 8 for detailed analysis.) . Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-23-aia AIA The factual inquiries set forth in Graham v. John Deere Co. , 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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. 07-21-aia AIA Claim 4 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Lachinski et al. (US Patent 12,566,899 B2) in view of Blondel et al. (US Pub 2023/0063306 A1) . As to claim 4 , claim 1 is incorporated and Lachinski discloses maintaining a database of removed objects of the 3D scene (Col 2, lines 62-65, “The system uses a change management system to catalog data changes from any of the databases within the system that have published work” Col 9, lines 36-47, “The Change Management module is responsible for identifying changes 505 by comparing versions of data within a database 503, a current version to the latest version 504 and when a change is validated 511 it is cataloged 507 and the data is stored on a server with a change type, date/time stamp/, userID, data sourceID, and status”) and, Lachinski does not discloses when a new object is detected, searching for an occurrence of the new object in the database. Blondel teaches when a new object is detected, searching for an occurrence of the new object in the database (Blondel, abstract, “performing a 3D match search in a 3D database using the 3D points cloud reconstruction, to identify the object, the 3D match search comprising a comparison of the reconstructed 3D points cloud of the object with 3D points clouds of known objects stored in the 3D database.” ¶0087, “The reconstructed 3D points cloud 1050 is forwarded to the storage server 30 for a 3D match search. The 3D match search is done with a 3D points cloud comparison made using the ply files. The comparison compares the user-generated ply file 1050 with known ply files 1052 stored in the 3D database 38.”). Lachinski and Blondel are considered to be analogous art because all pertain to 3D object reconstruction. It would have been obvious before the effective filing date of the claimed invention to have modified Lachinski with the features of “when a new object is detected, searching for an occurrence of the new object in the database” as taught by Blondel. The suggestion/motivation would have been in order to identify the object (Blondel, abstract.). As to claim 12 , claim 9 is incorporated and the combination of Lachinski and Blondel discloses the device is further configured for maintaining a database of removed objects of the 3D scene and, when a new object is detected, searching for an occurrence of the new object in the database (See claim 4 for detailed analysis.) . 07-21-aia AIA Claim 6 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Lachinski et al. (US Patent 12,566,899 B2) in view of Schickel (US Pub 2018/0196261 A1) . As to claim 6 , claim 5 is incorporated and Lachinski does not disclose the highlighting of the differences is displayed on a static RGB(D) frame in which the differences are fully visible. Schickel teaches the highlighting of the differences is displayed on a static RGB(D) frame in which the differences are fully visible (Schichel, ¶0057, “capture 30 frames of said scene per second, and to generate a corresponding 3D model of the scene for each frame and to describe it by means of the vertices and color values. The data which is thus generated for each frame (each single image) includes, as was mentioned above, the color values and the depth information, e.g., RGB values and X Y and Z values, each of which defines a vertex, the plurality of vertices forming a point cloud.” ¶0089, “the present embodiments are applied in surveillance as depiction and transmission of changing contents. For some applications, surveillance, recognition and transmission of changing contents are particularly important. In this context, differences of a static 3D model within specific limits (threshold values) as compared to a captured live image are generated so as to recognize any changes faster and more accurately than in a 2D video recording. For example, let us look at surveillance of a drilling rig. A static 3D model of the drilling rig is compared to a 3D image from an angle of view toward the drilling rig several times per second; for example, the drilling rig may be animated via the 3D engine during runtime. Any changes which occur in the live 3D model, such as a person entering into a picture-taking area, are compared to the static 3D model and may trigger alerts. For a 3D vision of the situation and of the location of the rig including the person, only transmission of the differences may be used since the static rig already exists as a 3D model, which is advantageous as compared to complete video transmission with regard to the amount of data, the speed, the 3D spatial view with an interactive visual focus and with an interactive quality of depiction, and to the quality of visualization.”). Lachinski and Schickel are considered to be analogous art because all pertain to 3D object reconstruction. It would have been obvious before the effective filing date of the claimed invention to have modified Lachinski with the features of “the highlighting of the differences is displayed on a static RGB(D) frame in which the differences are fully visible” as taught by Schickel. The suggestion/motivation would have been in order to recognize any changes faster and more accurately (Schickel, ¶0089). As to claim 14 , claim 13 is incorporated and the combination of Lachinski and Schickel discloses the highlighting of the differences is displayed on a static RGB(D) frame in which the differences are fully visible (See claim 6 for detailed analysis.) . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Sadalgi et al. (US Pub 2024/0193886 A1) teaches an interactive user interface that allows a user to perform one or more actions with respect at least one of the multiple spaces, the interactive user interface comprising a visualization of a first space of the multiple spaces; obtaining, based on user input provided through the interactive user interface, an indication of a first product and a first position in the visualization of the first space at which to insert a visualization of the first product. Totty et al. (US Patent 11,367,250 B2) teaches generating a virtual room model, generating a virtual room visual representation, providing the room data to a display device, receiving a virtual object selection, rendering an updated virtual room visual representation based on the virtual object. Any inquiry concerning this communication or earlier communications from the examiner should be directed to YU CHEN whose telephone number is (571)270-7951. The examiner can normally be reached on M-F 8-5 PST Mid-day flex. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Xiao Wu can be reached on 571-272-7761. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /YU CHEN/Primary Examiner, Art Unit 2613 Application/Control Number: 18/872,862 Page 2 Art Unit: 2613 Application/Control Number: 18/872,862 Page 3 Art Unit: 2613 Application/Control Number: 18/872,862 Page 4 Art Unit: 2613 Application/Control Number: 18/872,862 Page 5 Art Unit: 2613 Application/Control Number: 18/872,862 Page 6 Art Unit: 2613 Application/Control Number: 18/872,862 Page 7 Art Unit: 2613 Application/Control Number: 18/872,862 Page 8 Art Unit: 2613 Application/Control Number: 18/872,862 Page 9 Art Unit: 2613 Application/Control Number: 18/872,862 Page 10 Art Unit: 2613 Application/Control Number: 18/872,862 Page 11 Art Unit: 2613 Application/Control Number: 18/872,862 Page 12 Art Unit: 2613 Application/Control Number: 18/872,862 Page 13 Art Unit: 2613 Application/Control Number: 18/872,862 Page 14 Art Unit: 2613 Application/Control Number: 18/872,862 Page 15 Art Unit: 2613 Application/Control Number: 18/872,862 Page 16 Art Unit: 2613
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