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
Received 10/08/2025
Claim(s) 1-20 is/are pending.
Claim(s) 1, 2, 4, 7, 9-11, 18, and 19 has/have been amended.
The 35 U.S.C § 103 rejection to claim(s) 1-20 have been fully considered in view of the amendments received on 10/08/2025 and are fully addressed in the prior art rejection below.
Response to Arguments
Received 10/08/2025
Regarding independent claim(s) 1, 10, and 18:
Applicant’s arguments (Remarks, Page 8: ¶ 3), filed 10/08/2025, with respect to the rejection(s) of claim(s) 1, 10, and 18 under 35 U.S.C § 103 have been fully considered and are persuasive. Wherein, Wong et al. (US PGPUB No. 20210004933 A1) fails to disclose the subject matter of selectively applying, responsive to the specified type of the interior space and by accessing a data structure associating respective trained classification models with types of interior spaces, one or more trained classification models to identify at least one object in the panorama image. Therefore, the rejection has been withdrawn, necessitated by Applicant's amendments. However, upon further consideration, a new ground(s) of rejection is made in view of Wong et al., in view of Cier et al. (US PGPUB No. 20210127060 A1), in view of Segev et al. (US PGPUB No. 20210073449 A1), and further in view of ji et al. (US PGPUB No. 20210127060 A1).
Regarding dependent claim(s) 4, 7, and 9:
Applicant’s arguments (Remarks, Page 8: ¶ 3), filed 10/08/2025, with respect to the rejection(s) of claim(s) 4, 7, and 9 under 35 U.S.C § 103 have been fully considered and are persuasive due the dependency upon claims 1, 10, and 18 respectively. Additionally, the one or more limitations related to measurement overcome the teaches of Wong et al. Therefore, the rejection has been withdrawn, necessitated by Applicant's amendments. However, upon further consideration, a new ground(s) of rejection is made in view of the prior art as mentioned above and even further in view of Jovanovic et al. (US PGPUB No. 20190051054 A1).
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).
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.
Claim(s) 1, 5, 6, 8, 10, and 13-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over by Wong et al., US PGPUB No. 20210004933 A1, hereinafter Wong, in view of Cier et al., US PGPUB No. 20210127060 A1, hereinafter Cier, in view of Segev et al., US PGPUB No. 20210073449 A1, hereinafter Segev, and further in view of ji et al., US PGPUB No. 20210127060 A1, hereinafter ji.
Regarding claim 10, Wong discloses a system (Wong; a system [¶ 0030, ¶ 0036-0037, and ¶ 0042], as illustrated within Fig. 2), comprising:
a processor (Wong; the system [as addressed above] comprises a processor [¶ 0182]);
a memory with instructions stored therein that, when executed by the processor, cause a computing device to perform (Wong; the system [as addressed above] comprises a memory with instructions stored therein that cause a computing device to perform [¶ 0040, ¶ 0042, and ¶ 0044] when executed by the processor [¶ 0182]) a method (Wong the system executed by a processor [as addressed above] to perform a method [¶ 0182-0183]; moreover, method performed by a suitable system [¶ 0029-0030 and ¶ 0036]) of:
receiving input that is indicative of a request for assisted image capture of one or more objects located in an interior space (Wong; the method [as addressed above] configured for receiving input that is indicative of a request for assisted image capture of one or more objects located in an interior space [¶ 0031, ¶ 0033-0034, and ¶ 0051-0052], as illustrated within Fig. 3; moreover, obtaining a set of images [¶ 0048] in relation with a guided capture [¶ 0031 and ¶ 0063]);
instructing a user to systematically pan a camera around the interior space (Wong; the method [as addressed above] configured for instructing a user to systematically pan a camera around the interior space [¶ 0063-0065], as illustrated within Fig. 8; moreover, indoor panoramas [¶ 0033-0034 and ¶ 0052]);
acquiring, by the camera, a panorama image of the interior space (Wong; the method [as addressed above] configured for acquiring a panorama image of the interior space [¶ 0063-0065] by the camera [¶ 0038 and ¶ 0048]);
applying one or more trained classification models to identify at least one object in the panorama image (Wong; the method [as addressed above] configured for applying one or more trained classification models to identify at least one object in the panorama image [¶ 0074-0076]; moreover, extracting features from the set images [¶ 0071-0073]); and
causing display of at least a portion of the panorama image with a graphical element overlaid thereon that identifies the at least one object (Wong; the method [as addressed above] configured for causing display of at least a portion of the panorama image with a graphical element overlaid thereon that identifies the at least one object [¶ 0031, ¶ 0052-0053, and ¶ 0063-0064], as illustrated within Fig. 3; moreover, alignment of images [¶ 0029, ¶ 0070, and ¶ 0078-0080]).
Wong fails to disclose receiving, via a graphical user interface (GUI), input, wherein the input includes a specification of a type of the interior space;
displaying, on the GUI, instructions;
acquiring a panorama image of the interior space concurrently with inertial data generated by an inertial sensor of the computing device;
selectively applying, responsive to the specified type of the interior space and by accessing a data structure associating respective trained classification models with types of interior spaces, one or more trained classification models to identify at least one object in the panorama image; and
a graphical element comprising a bounding box overlaid thereon that identifies the at least one object.
However, Cier teaches receiving, via a graphical user interface (GUI), input that is indicative of a request for assisted image capture of one or more physical structures located in an interior space (Cier; receiving input that is indicative of a request for assisted image capture of one or more physical structures located in an interior space [¶ 0026-0028 and ¶ 0031-0032], as illustrated within Figs. 1A-B, via a GUI [¶ 0011]; moreover, to a Mobile Image Capture and Analysis (“MICA”) system [¶ 0012 and ¶ 0027-0028], further corresponding to one or more other systems [¶ 0024 and ¶ 0030-0033]; wherein, image capturing is at different angles [¶ 0036 and ¶ 0044], as illustrated within Fig. 2H; and wherein, a GUI is utilized to visually interact [¶ 0054-0055], as illustrated within 2K), wherein the input includes a specification of a type of the interior space (Cier; the input includes a specification of a type of the interior space [¶ 0028, ¶ 0032, and ¶ 0054-0055]; wherein, providing instructions for creating building floor plans, providing information to include with created building floor plans, obtaining and optionally interacting with one or more particular identified floor plans and/or with additional associated information [¶ 0028]; moreover, functionality of a MICA system (further correlated with a BICA system) [¶ 0030 and ¶ 0034]);
displaying, on the GUI, instructions to systematically pan a camera around the interior space (Cier; displaying instructions to systematically pan a camera around the interior space on the GUI [¶ 0038-0041], as illustrated within Figs. 2A-E; moreover, MICA system routine [¶ 0064] involving instructions or information [¶ 0065-0066 and ¶ 0069]; additionally, guidance cues (to a user) [¶ 0072]);
acquiring, by the camera, a panorama image of the interior space concurrently with inertial data generated by an inertial sensor of the computing device (Cier; acquiring a panorama image of the interior space [¶ 0022-0023] concurrently with inertial data generated by an inertial sensor of the computing device by the camera [¶ 0031-0033 and ¶ 0050]; moreover, image data and IMU data [¶ 0020, ¶ 0022, and ¶ 0027], as illustrated within Fig. 2I).
Wong and Cier are considered to be analogous art because both pertain to generating and/or managing data in relation with providing modeling data to a user, wherein one or more computerized units are utilized in order to produce a visualization effect.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong, to incorporate receiving, via a graphical user interface (GUI), input that is indicative of a request for assisted image capture of one or more physical structures located in an interior space, wherein the input includes a specification of a type of the interior space; displaying, on the GUI, instructions to systematically pan a camera around the interior space; acquiring, by the camera, a panorama image of the interior space concurrently with inertial data generated by an inertial sensor of the computing device (as taught by Cier), in order to provide an improved capturing of environments in an efficient manner (Cier; [¶ 0003]).
Wong as modified by Cier fails to disclose selectively applying, responsive to the specified type of the interior space and by accessing a data structure associating respective trained classification models with types of interior spaces, one or more trained classification models to identify at least one object in the panorama image; and
a graphical element comprising a bounding box overlaid thereon that identifies the at least one object.
However, Segev teaches selectively applying, responsive to the specified type of the interior space and by accessing a data structure associating respective trained classification models with types of interior spaces, one or more trained classification models to identify at least one object in the panorama image (Segev; selectively applying one or more trained classification models to identify at least one object in the panorama image [¶ 0136 and ¶ 0160] responsive to the specified type of the interior space and by accessing a data structure associating respective trained classification models with types of interior spaces [¶ 0162, ¶ 0164, and ¶ 0336-0337]; wherein, classifications can be made by text and/or image [¶ 0339 and ¶ 0341-0343] as well as geometric data [¶ 0344-0346]; moreover, architectural features of a floor plan [¶ 0347-0349]; moreover, an ANN [¶ 0128-0130], wherein a ML model can be combined with a geometric analysis and/or semantic analysis [¶ 0132 and ¶ 0392]; additionally, a ML model can be used to identify ideal locations/positions for sensor coverage [¶ 0204-0205] and to identify one or more objects [¶ 0230-0233]; even further, identifying one or more disinterests (or interests) [¶ 0234-0235 and ¶ 0241] as well as topological analysis [¶ 0242]; wherein, classification algorithm [¶ 0400-0401 and ¶ 0404] can be one or more data-structures [¶ 0402]); and
at least a portion of the panorama image with a graphical element comprising a bounding box overlaid thereon that identifies the at least one object (Segev; at least a portion of the panorama image with a graphical element comprising a bounding box overlaid thereon (corresponding to object recognition techniques know to one of ordinary skill in the art) that identifies the at least one object [¶ 0208-0209 and ¶ 0212-0213]; wherein, annotation corresponding to masks or bounding boxes [¶ 0131 and ¶ 0403]; moreover, image recognition algorithm [¶ 0226, ¶ 0230-0231, and ¶ 0233], and trained recognition [¶ 0336]; such that, a BIM object may include technical characteristics such as visualization data that gives the object a recognizable appearance and behavioral data, such as detection zones, which enable the object's position to be determined [¶ 0122, ¶ 0134, and ¶ 0396]).
Wong in view of Cier and Segev are considered to be analogous art because they pertain to generating and/or managing data in relation with providing modeling data to a user, wherein one or more computerized units are utilized in order to produce a visualization effect.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, to incorporate selectively applying, responsive to the specified type of the interior space and by accessing a data structure associating respective trained classification models with types of interior spaces, one or more trained classification models to identify at least one object in the panorama image; and at least a portion of the panorama image with a graphical element comprising a bounding box overlaid thereon that identifies the at least one object (as taught by Segev), in order to provide an improved computational efficiency, produce more optimal solutions, and allow for greater customization (Segev; [¶ 0003-0004 and ¶ 0094-0096]).
Wong as modified by Cier and Segev fails to explicitly disclose causing a display of a graphical element comprising a bounding box overlaid thereon.
However, Ji teaches receiving, via a graphical user interface (GUI), input that is indicative of a request for assisted image capture of one or more objects physical structures located in an interior space (Ji; receiving input that is indicative of a request for assisted image capture of one or more objects physical structures located in an interior [¶ 0085-0086 and ¶ 0089] space via a GUI [¶ 0082-0083], as illustrated with Fig. 15);
acquiring, by the camera, a panorama image of the interior space (Ji; acquiring a panorama image of the interior space [¶ 0085 and ¶ 0089] by the camera [¶ 0036-0037 and ¶ 0082-0083]); and
causing display of at least a portion of the panorama image with a graphical element comprising a bounding box overlaid thereon that identifies the at least one object (Ji; causing display of at least a portion of the panorama image with a graphical element comprising a bounding box overlaid thereon that identifies the at least one object [¶ 0083 and ¶ 0088-0094]; moreover, Manhattan-World structural features of surfaces [¶ 0039-0040 and ¶ 0043-0044]).
Wong in view of Cier and Segev and Ji are considered to be analogous art because they pertain to generating and/or managing data in relation with providing modeling data to a user, wherein one or more computerized units are utilized in order to produce a visualization effect.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier and Segev, to incorporate receiving, via a graphical user interface (GUI), input that is indicative of a request for assisted image capture of one or more objects physical structures located in an interior space; acquiring, by the camera, a panorama image of the interior space; and causing display of at least a portion of the panorama image with a graphical element comprising a bounding box overlaid thereon that identifies the at least one object (as taught by Ji), in order to provide three-dimensional modeling that is intuitive to a user in a less time-consuming and effort-intensive manner (Ji; [¶ 0004-0005 and ¶ 0011]).
Regarding claim 13, Wong in view of Cier, Segev, and Ji further discloses the system of claim 10, further comprising generating an equirectangular panorama image by temporally aligning inertial data with at least two images acquired by the camera (Wong; generating an equirectangular panorama image by temporally aligning inertial data with at least two images acquired by the camera [¶ 0031 and ¶ 0051-0052], as illustrated within Fig. 3).
Cier further teaches generating a panorama image by temporally aligning inertial data with at least two images acquired by the camera (Cier; generating a panorama image by temporally aligning inertial data with at least two images [¶ 0017-0019] acquired by the camera [¶ 0027, ¶ 0036, and ¶ 0046-0048]; wherein, the MICA system receives constituent images captured by the imaging system on the mobile device, and obtains corresponding IMU data from sensor modules for each such constituent image [¶ 0020], wherein IMU motion data is utilized as part of the translational motion alignment for two or more constituent images (e.g., for constituent image slices selected for adjacent angular slots) [¶ 0050]; moreover, final stitching phase [¶ 0051]; moreover, performing analysis in order to inter-connect (or link) panoramas together wherein one or more cameras and/or IMUs are utilized [¶ 0031-0033]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, Segev, and Ji, to incorporate generating a panorama image by temporally aligning inertial data with at least two images acquired by the camera (as taught by Cier), in order to provide an improved capturing of environments in an efficient manner (Cier; [¶ 0003]).
Regarding claim 14, Wong in view of Cier, Segev, and Ji further discloses the system of claim 10, further comprising configuring a capture parameter of the camera (Wong; configuring a capture parameter of the camera [¶ 0059-0061]), wherein the capture parameter comprises one or more of camera resolution, focus, and flash (Wong; the capture parameter comprises one or more of camera resolution, focus, and flash [¶ 0060-0061]), and further acquiring inertial data and the panorama image of the interior space according to the capture parameter (Wong; further acquiring inertial data [¶ 0038 and ¶ 0042] and the panorama image of the interior space according to the capture parameter [¶ 0060-0061 and ¶ 0063]; moreover, capturing of indoor spaces [¶ 0031, ¶ 0033-0034, and ¶ 0052]).
Regarding claim 15, Wong in view of Cier, Segev, and Ji further discloses the system of claim 10, further comprising:
determining spatial positions of one or more junctures of the panorama image (Wong; determining spatial positions of one or more junctures of the panorama image [¶ 0082-0084]; moreover, image alignment using one or more images [¶ 0085-0087] in relation with a panorama image [¶ 0051 and ¶ 0070], as illustrated within Fig. 3 and Fig. 9C); and
calculating dimensions of the interior space based on the spatial positions (Wong; calculating dimensions (i.e. translation) of the interior space based on the spatial positions [¶ 0052-0053, ¶ 0057, ¶ 0063-0064, and ¶ 0081-0082]).
Regarding claim 16, Wong in view of Cier, Segev, and Ji further discloses the system of claim 15, wherein each juncture represents a floor-wall boundary at which a floor and a wall join, a ceiling-wall boundary at which a ceiling and a wall join, or a wall-wall boundary at which a pair of walls join (Wong; each juncture represents a floor-wall boundary at which a floor and a wall join, a ceiling-wall boundary at which a ceiling and a wall join, or a wall-wall boundary at which a pair of walls join [¶ 0052, ¶ 0064, and ¶ 0096]).
Regarding claim 17, Wong in view of Cier, Segev, and Ji further discloses the system of claim 10, wherein the one or more trained classification models perform pixel-wise classification of pixel data corresponding to one or more of the panorama image and an equirectangular panorama image (Wong; the one or more trained classification models perform pixel-wise classification of pixel data [¶ 0074] corresponding to one or more of the panorama image and an equirectangular panorama image [¶ 0031 and ¶ 0070]; additionally, matching features [¶ 0078, ¶ 0088, and ¶ 0091-0094]).
Segev further teaches the one or more trained classification models perform pixel-wise classification of pixel data corresponding to one or more of the panorama image (Segev; the one or more trained classification models [¶ 0129-0130 and ¶ 0132] implicitly perform pixel-wise classification of pixel data (given image processing techniques) corresponding to one or more of the panorama image [¶ 0212-0214]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, Segev, and Ji, to incorporate the one or more trained classification models perform pixel-wise classification of pixel data corresponding to one or more of the panorama image (as taught by Segev), in order to provide an improved computational efficiency, produce more optimal solutions, and allow for greater customization (Segev; [¶ 0003-0004 and ¶ 0094-0096]).
Regarding claim 1, the rejection of claim 1 is addressed within the rejection of claim 10, due to the similarities claim 1 and claim 10 share, therefore refer to the rejection of claim 10 regarding the rejection of claim 1. Although, claim 1 and claim 10 may not be identical, they are considerably comparable or substantially equivalent given their overlapping subject matter. Thus, it is reasonable to reject claim 1 based on the teachings and rational in relation with the prior art within the rejection of claim 10.
Regarding claim 5, the rejection of claim 5 is addressed within the rejection of claim 14, due to the similarities claim 5 and claim 14 share, therefore refer to the rejection of claim 14 regarding the rejection of claim 5.
Regarding claim 6, the rejection of claim 6 is addressed within the rejection of claim 14, due to the similarities claim 6 and claim 14 share, therefore refer to the rejection of claim 14 regarding the rejection of claim 6.
Regarding claim 8, the rejection of claim 8 is addressed within the rejection of claim 16, due to the similarities claim 8 and claim 16 share, therefore refer to the rejection of claim 16 regarding the rejection of claim 8.
Regarding claim 18, the rejection of claim 18 is addressed within the rejection of claim 10, due to the similarities claim 18 and claim 10 share, therefore refer to the rejection of claim 10 regarding the rejection of claim 18; however, the subject matter/limitations not addressed by claim 10 is/are addressed below.
Wong discloses a non-transitory medium with instructions stored thereon that, when executed by a processor of a computing device, cause the computing device to perform operations (Wong; a non-transitory medium with instructions stored thereon that cause the computing device to perform operations when executed by a processor of a computing device [¶ 0182]).
(further refer to the rejection of claim 10)
Claim(s) 4, 7, and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wong in view of Cier, Segev, and Ji as applied to claim(s) 1 above, and further in view of Jovanovic et al., US PGPUB No. 20190051054 A1, hereinafter Jovanovic.
Regarding claim 4, the rejection of claim 4 is addressed within the rejection of claim 13, due to the similarities claim 4 and claim 13 share, therefore refer to the rejection of claim 13 regarding the rejection of claim 4; however, the subject matter/limitations not addressed by claim 4 is/are addressed below.
Cier discloses wherein the inertial data is used to estimate an absolute measurements of the one or more physical structures relative to a distance between the computing device and a surface (Cier; the inertial data [as addressed within the parent claim(s)] is used to estimate an absolute measurements of the one or more physical structures relative to a distance between the computing device and a surface [¶ 0027 and ¶ 0031]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, Segev, and Ji, to incorporate the inertial data is used to estimate an absolute measurements of the one or more physical structures relative to a distance between the computing device and a surface (as taught by Cier), in order to provide an improved capturing of environments in an efficient manner (Cier; [¶ 0003]).
Wong as modified by Cier, Segev, and Ji fails to disclose to estimate a scale factor for absolute measurements of the one or more physical structures relative to a distance between the computing device and a ground surface.
However, Jovanovic teaches the inertial data is used to estimate a scale factor for absolute measurements of the one or more physical structures relative to a distance between the computing device and a ground surface (Jovanovic; the inertial data is used to estimate a scale factor for absolute measurements of the one or more physical structures [¶ 0073-0075] relative to a distance between the computing device and a ground surface (i.e. floor-to-ceiling) [¶ 0079-0082]; moreover, measuring [¶ 0083-0084]; wherein, an AR application utilizes a resource of the smartphone to identify the position and orientation of the smartphone in reference to a fixed coordinate system as well as the orientation of the ground plane in the space in reference to the fixed coordinate system [¶ 0085], in relation with measuring floor-to-ceiling [¶ 0047-0048 and ¶ 0086-0088]).
Wong in view of Cier, Segev, and Ji and Jovanovic are considered to be analogous art because they pertain to generating and/or managing data in relation with providing modeling data to a user, wherein one or more computerized units are utilized in order to produce a visualization effect.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, Segev, and Ji, to incorporate the inertial data is used to estimate a scale factor for absolute measurements of the one or more physical structures relative to a distance between the computing device and a ground surface (as taught by Jovanovic), in order to provide floorplans that reduce resource consumption and drifting errors (Jovanovic; [¶ 0002 and ¶ 0005]).
(further refer to the rejection of claim 13)
Regarding claim 7, Wong in view of Cier, Segev, and Ji further discloses the method of claim 1, further comprising:
determining spatial positions of one or more junctures of the panorama image (Wong; determining spatial positions of one or more junctures of the panorama image [¶ 0082-0084]; moreover, image alignment using one or more images [¶ 0085-0087] in relation with a panorama image [¶ 0051 and ¶ 0070], as illustrated within Fig. 3 and Fig. 9C); and
calculating dimensions of the interior space based on the spatial positions (Wong; calculating dimensions (i.e. translation) of the interior space based on the spatial positions [¶ 0052-0053, ¶ 0057, ¶ 0063-0064, and ¶ 0081-0082]).
Cier further teaches determining spatial positions of one or more junctures of the panorama image using a trained model that predicts the spatial positions in near real time during the systematic panning (Cier; determining spatial positions of one or more junctures/links of the panorama image using an automation (i.e. automated determination) [¶ 0036-0039] that predicts/calculates the spatial positions in near real time during the systematic panning (i.e. capture sequence) [¶ 0044 and ¶ 0049-0051]; wherein, using a trained model is implicit, given automated determination [¶ 0020 and ¶ 0032] associated with MICA [¶ 0070-0071]; and wherein, automation is performed in real-time / near-real-time [¶ 0011-0012]; moreover, generating panorama images through data capture [¶ 0033-0034] and the process of linking images [¶ 0055-0056]); and
calculating dimensions of the interior space based on the spatial positions (Cier; calculating dimensions of the interior space based on the spatial positions [¶ 0055-0056]; moreover, MIGM [¶ 0023]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, Segev, and Ji, to incorporate determining spatial positions of one or more junctures of the panorama image using a trained model that predicts the spatial positions in near real time during the systematic panning; and calculating dimensions of the interior space based on the spatial positions (as taught by Cier), in order to provide an improved capturing of environments in an efficient manner (Cier; [¶ 0003]).
Wong in view of Cier, Segev, and Ji fails to disclose to enable measurement of arbitrary angles or square footage.
However, Jovanovic teaches calculating dimensions of the interior space based on the spatial positions to enable measurement of arbitrary angles or square footage (Jovanovic; calculating dimensions of the interior space based on the spatial positions to enable measurement of arbitrary angles or square footage [¶ 0044-0046]; moreover, linear segmental measurements [¶ 0086-0087] that are visualized using an arbitrary angles or square footage (wherein, scale or unit of measure is arbitrary given one of ordinary skill in the art understands unit conversions) [¶ 0062, ¶ 0079-0080 and ¶ 0089-0090], as illustrated within Fig. 9, Fig. 20, and Fig. 27).
Wong in view of Cier, Segev, and Ji and Jovanovic are considered to be analogous art because they pertain to generating and/or managing data in relation with providing modeling data to a user, wherein one or more computerized units are utilized in order to produce a visualization effect.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, Segev, and Ji, to incorporate calculating dimensions of the interior space based on the spatial positions to enable measurement of arbitrary angles or square footage (as taught by Jovanovic), in order to provide floorplans that reduce resource consumption and drifting errors (Jovanovic; [¶ 0002 and ¶ 0005]).
Regarding claim 9, the rejection of claim 9 is addressed within the rejection of claim 17, due to the similarities claim 9 and claim 17 share, therefore refer to the rejection of claim 17 regarding the rejection of claim 9; however, the subject matter/limitations not addressed by claim 17 is/are addressed below.
Segev further teaches to define boundaries of the at least one object for dimension (Segev; to define boundaries of the at least one object for dimension [¶ 0132 and ¶ 0204]; moreover, identifying wall boundaries using a ML model [¶ 0014 and ¶ 0124]; even further, semantic and/or geometric analysis [¶ 0133-0136]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, Segev, and Ji, to incorporate to define boundaries of the at least one object for dimension (as taught by Segev), in order to provide an improved computational efficiency, produce more optimal solutions, and allow for greater customization (Segev; [¶ 0003-0004 and ¶ 0094-0096]).
Wong as modified by Cier, Segev, and Ji fails to disclose a scale factor estimated from the inertial data.
However, Jovanovic teaches to define boundaries of the at least one object for dimension estimation relative to a scale factor estimated from the inertial data (Jovanovic; to define boundaries (i.e. edges, dimensions) of the at least one object for dimension estimation [¶ 0079-0083] relative to a scale factor estimated from the inertial data [¶ 0073-0075]; moreover, measurements and linear segments involving user interaction [¶ 0085-0087], wherein user interaction further involves motion [¶ 0042-0043 and ¶ 0047-0048]).
Wong in view of Cier, Segev, and Ji and Jovanovic are considered to be analogous art because they pertain to generating and/or managing data in relation with providing modeling data to a user, wherein one or more computerized units are utilized in order to produce a visualization effect.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, Segev, and Ji, to incorporate to define boundaries of the at least one object for dimension estimation relative to a scale factor estimated from the inertial data (as taught by Jovanovic), in order to provide floorplans that reduce resource consumption and drifting errors (Jovanovic; [¶ 0002 and ¶ 0005]).
(further refer to the rejection of claim 17)
Claim(s) 2, 3, 11, 12, 19, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wong in view of Cier, Segev, and Ji as applied to claim(s) 1, 10, and 18 above, and further in view of Chasko, US PGPUB No. 20200251220 A1, hereinafter Chasko.
Regarding claim 11, Wong in view of Cier, Segev, and Ji further discloses the system of claim 10, wherein the graphical element identifies an abnormal appearance of the at least one object (Wong; the graphical element identifies the implicit abnormal appearance (given the one or more warnings) of the at least one object [¶ 0063-0064]; additionally, the term of abnormal has relative meaning, and without proper context or reference is subjective).
Segev further teaches identifying an abnormal appearance of the at least one object (Segev; identifying an implicit abnormal appearance (given an interest/disinterest) of the at least one object [¶ 0007-0008 and ¶ 0097]; wherein, a marked area may define an area of interest or disinterest within at least one room, and an area of interest (AOI) or area of disinterest (AOD) may be an area upon which functional requirements or technical characteristics are applied and may differ from the functional requirement applied to another area of the room [¶ 0223-0225]; moreover, area of disinterest [¶ 0230-0231, ¶ 0234, and ¶ 0285-0286]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, Segev, and Ji, to incorporate identifying an abnormal appearance of the at least one object (as taught by Segev), in order to provide an improved computational efficiency, produce more optimal solutions, and allow for greater customization (Segev; [¶ 0003-0004 and ¶ 0094-0096]).
Wong as modified by Cier, Segev, and Ji fails to explicitly disclose an abnormal appearance.
However, Chasko teaches identifying an abnormal appearance of the at least one object (Chasko; identifying an abnormal appearance of the at least one object [¶ 0019-0020 and ¶ 0025-0026]).
Wong in view of Cier, Segev, and Ji and Chasko are considered to be analogous art because they pertain to generating and/or managing data in relation with providing modeling data to a user, wherein one or more computerized units are utilized in order to produce a visualization effect.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, Segev, and Ji, to incorporate identifying an abnormal appearance of the at least one object (as taught by Chasko), in order to provide information that improves an environment by assessing potential risk (Chasko; [¶ 0002-0006 and ¶ 0018]).
Regarding claim 12, Wong in view of Cier, Segev, Ji, and Chasko further discloses the system of claim 10, wherein the graphical element identifies one or more risks or hazards associated with the at least one object (Wong; the graphical element identifies one or more implicit risks or hazards (given the one or more warnings) associated with the at least one object [¶ 0063-0064]; additionally, the terms of risk and/or hazard have relative meaning, and without proper context or reference are subjective).
Segev further teaches identifying one or more risks or hazards associated with the at least one object (Segev; identifying one or more implicit risks or hazards (given an interest/disinterest) associated with the at least one object [¶ 0007-0008 and ¶ 0097]; wherein, identifying functional requirements [¶ 0136 and ¶ 0224-0226]; moreover, an area of interest with a plurality of functional requirements [¶ 0227-0230]; moreover, area of disinterest [¶ 0230-0231, ¶ 0234, and ¶ 0285-0286]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, Segev, and Ji, to incorporate identifying one or more risks or hazards associated with the at least one object (as taught by Segev), in order to provide an improved computational efficiency, produce more optimal solutions, and allow for greater customization (Segev; [¶ 0003-0004 and ¶ 0094-0096]).
Wong in view of Cier, Segev, and Ji fails to explicitly disclose risks or hazards.
However, Chasko further teaches identifying one or more risks or hazards associated with the at least one object (Chasko; identifying one or more risks or hazards associated with the at least one object [¶ 0019-0020 and ¶ 0025-0026]).
Wong in view of Cier, Segev, and Ji and Chasko are considered to be analogous art because they pertain to generating and/or managing data in relation with providing modeling data to a user, wherein one or more computerized units are utilized in order to produce a visualization effect.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Wong as modified by Cier, Segev, and Ji, to incorporate identifying one or more risks or hazards associated with the at least one object (as taught by Chasko), in order to provide information that improves an environment by assessing potential risk (Chasko; [¶ 0002-0006 and ¶ 0018]).
Regarding claim 2, the rejection of claim 2 is addressed within the rejection of claim 11, due to the similarities claim 2 and claim 11 share, therefore refer to the rejection of claim 11 regarding the rejection of claim 2.
Regarding claim 3, the rejection of claim 3 is addressed within the rejection of claim 12, due to the similarities claim 3 and claim 12 share, therefore refer to the rejection of claim 12 regarding the rejection of claim 3.
Regarding claim 19, the rejection of claim 19 is addressed within the rejection of claim 11, due to the similarities claim 2 and claim 19 share, therefore refer to the rejection of claim 19 regarding the rejection of claim 2.
Regarding claim 20, the rejection of claim 20 is addressed within the rejection of claim 12, due to the similarities claim 20 and claim 12 share, therefore refer to the rejection of claim 12 regarding the rejection of claim 20.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Tung et al. (US Patent No. 10607405 B2).
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Refer to PTO-892, Notice of Reference Cited for a listing of analogous art.
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 Charles Lloyd Beard whose telephone number is (571)272-5735. The examiner can normally be reached Monday - Friday, 8:00 AM - 5: 00 PM, alternate Fridays EST.
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CHARLES LLOYD. BEARD
Primary Examiner
Art Unit 2611
/CHARLES L BEARD/ Primary Examiner, Art Unit 2611