DETAILED ACTION
The office action is responsive to a preliminary amendment filed on 11/28/22 and is being examined under the first inventor to file provisions of the AIA . Claims 1-20 are pending.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Under the broadest reasonable interpretation, the claims cover performance of the limitation in the mind or by pencil and paper.
Claims 1
Regarding step 1, claim 1 is directed towards a method and a system, which has the claim fall within the eligible statutory categories of processes, machines, manufactures and composition of matter under 35 U.S.C. 101.
Claim 1
Regarding step 2A, prong 1, claim 1 recites “generating a plurality of planes from the PC”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “determining those planes that are representative of objects to be included in the parametric structural design model and storing those planes in memory”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “determining those planes that are not representative of objects to be included in the parametric structural design model and discarding those planes”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Regarding step 2A, prong 2, the limitation of “receiving a point cloud (PC)
representation of the built structure” amounts to extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of “retrieving the properties of those objects to be included in the parametric structural design model from an Industry Foundation Classes (IFC) specification containing object property specifications” amounts to extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of “and generating the parametric structural design model with the planes representative of the objects to be included, and the properties of those objects from the IFC specification” amounts to mere instructions to apply an exception, where it recites an idea of a solution. The claim limitation doesn’t indicate what the planes are that represent the objects of model or what the properties of the objects are. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".
Further, the additional elements of a computer. The computer is recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a computer and/or a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Regarding Step 2B, the limitations of “receiving a point cloud (PC)
representation of the built structure” and “retrieving the properties of those objects to be included in the parametric structural design model from an Industry Foundation Classes (IFC) specification containing object property specifications” are also shown to reflect the court decisions of Versata Dev. Group, Inc. v. SAP Am., Inc. iv. Storing and retrieving information in memory, shown in MPEP 2106.05(d) (II).
Also, the limitation of “and generating the parametric structural design model with the planes representative of the objects to be included, and the properties of those objects from the IFC specification” amounts to mere instructions to apply an exception, where it recites an idea of a solution. The claim limitation doesn’t indicate what the planes are that represent the objects of model or what the properties of the objects are. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".
Further, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of the computer amounts no more than mere instructions to apply the exception using a generic computer component that does not impose any meaningful limits on practicing the abstract idea and therefore cannot provide an inventive concept (See MPEP 2106.05(b).
Claim 2
Dependent claim 2 recites “in claim 1 in which the PC contains a data set with a plurality of data points, one or more scan positions, a 3D coordinate value (XYZ), and a scan index value associated therewith.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 3
Dependent claim 3 recites “in claim 1 in which the method comprises the intermediate step of defining an arrangement graph.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 4
Dependent claim 4 recites “in which the method comprises the step of generating the parametric structural design model using the arrangement graph.”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The claim limitation doesn’t indicate what the data is within the arrangement graph. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".
Claim 5
Dependent claim 5 recites “in which the method comprises the additional intermediate step of: generating a plurality of IFC structural objects in addition to the walls, the floors and the ceilings, from the PC.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 6
Dependent claim 6 recites “generating the parametric structural design model with the plurality of IFC structural objects, and the properties of those objects from the IFC specification.”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The claim limitation doesn’t indicate what the objects or the properties of the objects are. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".
Claim 7
Dependent claim 7 recites “in which the parametric structural design model comprises an IFC model including an IFC schema file classifying all object types and object characteristics.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 8
Dependent claim 8 recites “in which the method comprises the intermediate step of, after receiving the PC, subsampling the PC data points according to a three-dimension (3D) voxel grid.”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The claim limitation doesn’t indicate how the three-dimension (3D) voxel grid is associated with the PC data points. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".
Claim 9
Dependent claim 9 recites “applying a normal estimation function across the subsampled PC data points”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The claim limitation doesn’t indicate how the normal estimation function is being applied across the subsampled PC data points. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".
Dependent claim 9 recites “and, assigning a 3D normal vector to each data point in addition to their 3D Cartesian coordinate.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 10
Dependent claim 10 recites “further comprising the step of planar object recognition including: defining each planar object as the equation of its plane, a surface normal vector and the set of data points that lie on its plane.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 11
Dependent claim 11 recites “defining a projection function from 3D to two dimension (2D) so that a data point may be mapped from 3D onto a flat 2D surface”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Dependent claim 11 recites “and defining a reprojection function from 2D to 3D so that the point may be mapped from a 2D plane into 3D space.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 12
Dependent claim 12 recites “comprising the step of projecting the points associated with a plane to 2D and re- projecting those points back into 3D in order to form the vertices of a simple rectangular collision mesh.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. The limitation doesn’t state how the projecting or the re-projecting is being conducted. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 13
Dependent claim 13 recites “in which the method comprises the step of collapsing all the data points into a 2D array”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. The limitation doesn’t state how the data points are being collapsed into a 2D array. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Dependent claim 13 recites “and applying a Gaussian smoothing technique to the 2D array.”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The claim limitation doesn’t indicate how the Gaussian smoothing technique is being applied to the 2D array. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".
Claim 14
Dependent claim 14 recites “the step of determining the planes not to be included in the parametric structural design model comprises determining those planes that are neither horizontal nor vertical.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 15
Dependent claim 15 recites “the step of determining the planes that are to be included in the parametric structural design model comprises determining those planes that are either vertical or horizontal.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. The limitation doesn’t state how the determining is being conducted. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 16
Dependent claim 16 recites “in which for those planes that are vertical, determining whether the vertical plane relates to one of an internal wall or an external wall.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. The limitation doesn’t state how the determining is being conducted. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 17
Dependent claim 17 recites “determining whether there is another vertical plane spaced apart from but within a threshold distance from the first vertical plane.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. The limitation doesn’t state how the determining is being conducted. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 18
Dependent claim 18 recites “in which for those planes that are horizontal, determining whether the horizontal plane relates to one of a ceiling, a floor or a slab intermediate floors.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. The limitation doesn’t state how the determining is being conducted. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 19
Dependent claim 19 recites “determining whether there is another horizontal plane spaced apart from but within a threshold distance from the first horizontal plane.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. The limitation doesn’t state how the determining is being conducted. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 20
Dependent claim 20 recites “the additional step of performing structure opening detection.”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The claim limitation doesn’t indicate how the performing of the structure opening detection is being conducted. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".
Claims 1-20 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 102
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 –
(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.
Claim(s) 1, 5-7 and 14-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated
by online reference Automatic Geometry Generation from Point Clouds for BIM, written by Thomson et al. (from IDS dated 3/11/24).
With respect to claim 1, Thomson et al. discloses “A computer implemented method
of generating a parametric structural design model from a built structure” as [Thomson et al. (Pg. 11755, sec. 1 Introduction, 1st paragraph, “Even though, from a BIM perspective, creating parametric 3D building models from scan data appears new, it actually extends back to the early days of commercialised terrestrial laser scanning systems creating parameterised surface representations from segmented point clouds [7] and goes back further than this in the aerial domain for external parametric reconstruction [8,9]. A system of note from the close-range photogrammetry domain is Hazmap; originally developed to facilitate the capture and parametric modelling of complex nuclear plants in the 1990s [10].”)];
“receiving a point cloud (PC) representation of the built structure” as [Thomson et al. (Pg. 11758, sec. 2.2.1 Reading In, “Loading the point cloud data into memory is the first step in the process. To keep with the non-proprietary, interoperable nature of BIM the E57 format was decided as the input format of choice to support. The LIBE57 library version 1.1.312 provided the necessary reader to interpret the E57 file format [42] and some code was written to transfer the E57 data into the PCL point cloud data structure. In this case, only the geometry was needed so only the coordinates were taken into the structure.”)];
“generating a plurality of planes from the PC” as [Thomson et al. (Pg. 11759, sec. 2.2.2, Plane Model Segmentation, 1st paragraph “With the data loaded in, the processing can begin. Firstly the major horizontal planes are detected as these likely represent the floor and ceiling components and then the vertical planes which likely represent walls (Figure 1b,c). The plane detection for both cases is done with the PCL implementation of RANSAC (RANdom SAmple Consensus) [43] due to the speed and established nature. The algorithm is constrained to accept only planes whose normal coefficient is within a three degree deviation from parallel to the Z-axis (up) for horizontal planes and perpendicular to Z for vertical planes.”, Fig. 1)];
“determining those planes that are representative of objects to be included in the parametric structural design model and storing those planes in memory” as [Thomson et al. (Pg. 11761, sec. 2.2.4 Spatial Reasoning, 1st paragraph, Extended large walls, “Large planes which do not extend fully from floor to ceiling are automatically extended so their lowest height is at floor level and highest is at ceiling level. For the experiments we chose walls that are greater than 1m in length or occupy 2/3 of the height between floor and ceiling levels.”, Thomson et al. (Pg. 11761, sec. 2.2.4 Spatial Reasoning, 1st paragraph, Merge close planes with similar normal, “Planes that have parallel normals and within an offset distance from each other are merged into one wall of overall thickness being the distance between the planes. If a plane pair is not found a default value of 100mm thickness is used.”)];
“determining those planes that are not representative of objects to be included in the parametric structural design model and discarding those planes” as [Thomson et al. (Pg. 11761, sec. 2.2.4 Spatial Reasoning, 1st paragraph, Reject small walls, “Planes that are too small in length or occupy too little of the height between floor and ceiling levels are removed from the model. For the experiments described here we chose 100mm as the minimum length and 1/3 of the floor to ceiling distance as the minimum height.”, The examiner considers the planes that are too small in length or occupy too little of height between the floor and ceiling levels that are removed to be the planes that are not representative of objects to be included in the parametric structural design model, since they are removed from the model)];
“retrieving the properties of those objects to be included in the parametric structural design model from an Industry Foundation Classes (IFC) specification containing object property specifications” as [Thomson et al. (Pgs. 11760-11761, sec. 2.2.3, 1st- 2nd paragraph, “With the relevant points that represent dominant planes extracted, the requisite dimensions needed for IFC geometry construction could be measured. This meant extracting a boundary for the slabs and a length and height extent for the walls; the reasons for this are provided in the next section.”, Thomson et al. (Pg. 11761, 1st paragraph, “We start by creating an initializing an empty model into which the IFC objects can be added. Each object is created from the information extracted previously by the segmentation code detailed in the last section. First the slabs are added by providing a boundary, extrusion depth or thickness and the level in Z at which he slab is extruded from. The walls are represented by their object dimensions (length, width, height) and a placement coordinate and rotation (bearing) of that footprint in the global coordinate system.”, The examiner considers the height and width of the walls to be the properties of the objects, since height and width of a wall can be properties for an object, see Pg. 24 last paragraph of the specification)];
“and generating the parametric structural design model with the planes representative of the objects to be included, and the properties of those objects from the IFC specification.” as [Thomson et al. (Pgs. 11760-11761, sec. 2.2.3, 1st- 2nd paragraph, “Each IFC object can be represented a few different ways (swept solid, brep, etc.) To create the IFC, the geometry of the elements needs to be constructing using certain dimensions. In this work the IFC object chosen for wall representation is IfcWallStandardCase, which handles all walls that are, etc.”)];
With respect to claim 5, Thomson et al. discloses “in which the method comprises the additional intermediate step of : generating a plurality of IFC structural objects in addition to the walls, the floors and the ceilings, from the PC.” as [Thomson et al. (Pg. 11761, sec. 2.2.3 IFC Generation, 2nd paragraph, “We start by creating an initializing an empty model into which the IFC objects can be added. Each object is created from the information extracted previously by the segmentation code detailed in the last section. First the slabs are added by providing a boundary, extrusion depth or thickness and the level in Z at which he slab is extruded from. The walls are represented by their object dimensions (length, width, height) and a placement coordinate and rotation (bearing) of that footprint in the global coordinate system.”)];
With respect to claim 6, Thomson et al. discloses “in which the step of generating the parametric structural design model further comprises generating the parametric structural design model with the plurality of IFC structural objects, and the properties of those objects from the IFC specification.” as [Thomson et al. (Pg. 11761, sec. 2.2.3 IFC Generation, 2nd paragraph, “We start by creating an initializing an empty model into which the IFC objects can be added. Each object is created from the information extracted previously by the segmentation code detailed in the last section. First the slabs are added by providing a boundary, extrusion depth or thickness and the level in Z at which he slab is extruded from. The walls are represented by their object dimensions (length, width, height) and a placement coordinate and rotation (bearing) of that footprint in the global coordinate system.”)];
With respect to claim 7, Thomson et al. discloses “in which the parametric structural design model comprises an IFC model including an IFC schema file classifying all object types and object characteristics.” as [Thomson et al. (Pg. 11761, sec. 2.2.4 Spatial Reasoning, last paragraph, “Once successfully created with or without geometric reasoning applied the walls and slabs can be stored to the model and saved as an IFC file. Figure 3 shows an example of the resultant geometry that is obtained through both processes. This file can then be viewed in any IFC viewer or BIM design tools such as Autodesk Revit.”, Thomson et al. (Pg. 11762, sec. 2.3.1 Reading the IFC, “We start by loading the IFC file into memory. Then, for each IFC object that is required, the coordinates of an object-oriented bounding box are extracted as the return geometry. A user specified tolerance can be added to take account of errors and generalisations made during modelling, thus enlarging the bounding boxes by that amount.”)];
With respect to claim 14, Thomson et al. discloses “in which the step of determining the planes not to be included in the parametric structural design model comprises determining those planes that are neither horizontal nor vertical.” as [Thomson et al. (Pg. 11759, sec. 2.2.2, 1st paragraph, “With the data loaded in, the processing can begin. Firstly the major horizontal planes are detected as these likely represent the floor and ceiling components and then the vertical planes which likely represent walls (Figure 1b,c).”)];
With respect to claim 15, Thomson et al. discloses “in which the step of determining the planes that are to be included in the parametric structural design model comprises determining those planes that are either vertical or horizontal.” as [Thomson et al. (Pg. 11759, sec. 2.2.2, 1st paragraph, “With the data loaded in, the processing can begin. Firstly the major horizontal planes are detected as these likely represent the floor and ceiling components and then the vertical planes which likely represent walls (Figure 1b,c).”)];
With respect to claim 16, Thomson et al. discloses “in which for those planes that are vertical, determining whether the vertical plane relates to one of an internal wall or an external wall.” as [Thomson et al. (Pg. 11759, sec. 2.2.2, 1st paragraph, “With the data loaded in, the processing can begin. Firstly the major horizontal planes are detected as these likely represent the floor and ceiling components and then the vertical planes which likely represent walls (Figure 1b,c).”, Fig, 1c))];
With respect to claim 17, Thomson et al. discloses “determining whether there is another vertical plane spaced apart from but within a threshold distance from the first vertical plane.” as [Thomson et al. (Pg. 11759, sec. 2.2.2, middle of 1st paragraph “The algorithm is constrained to accept only planes whose normal coefficient is within a three degree deviation from parallel to the Z-axis (up) for horizontal planes and perpendicular to Z for vertical planes. Also a distance threshold was set for the maximum distance of the points to the plane to accept as part of the model. Choosing this value is related to the noise level of the data from the instrument that was used for capture.”)];
With respect to claim 18, Thomson et al. discloses “in which for those planes that are horizontal, determining whether the horizontal plane relates to one of a ceiling, a floor or a slab intermediate floors.” as [Thomson et al. (Pg. 11759, sec. 2.2.2, 1st paragraph, “With the data loaded in, the processing can begin. Firstly the major horizontal planes are detected as these likely represent the floor and ceiling components and then the vertical planes which likely represent walls (Figure 1b,c).”, Fig, 1c))];
With respect to claim 19, Thomson et al. discloses “determining whether there is another horizontal plane spaced apart from but within a threshold distance from the first horizontal plane.” as [Thomson et al. (Pg. 11759, sec. 2.2.2, middle of 1st paragraph “The algorithm is constrained to accept only planes whose normal coefficient is within a three degree deviation from parallel to the Z-axis (up) for horizontal planes and perpendicular to Z for vertical planes. Also a distance threshold was set for the maximum distance of the points to the plane to accept as part of the model. Choosing this value is related to the noise level of the data from the instrument that was used for capture.”)];
With respect to claim 20, Thomson et al. discloses “the additional step of performing structure opening detection.” as [Thomson et al. (Pg. 11759, sec. 2.2.2, 1st paragraph, “With the data loaded in, the processing can begin. Firstly the major horizontal planes are detected as
these likely represent the floor and ceiling components and then the vertical planes which likely represent walls (Figure 1b,c). The plane detection for both cases is done with the PCL implementation of RANSAC (RANdom SAmple Consensus) [43] due to the speed and established nature. The algorithm is constrained to accept only planes whose normal coefficient is within a three degree deviation from parallel to the Z-axis (up) for horizontal planes and perpendicular to Z for vertical planes.”)];
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.
Claim(s) 2 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over online
reference Automatic Geometry Generation from Point Clouds for BIM, written by Thomson et al. (from IDS dated 3/11/24) in view of online reference From Point Clouds to Building Information Models: 3D Semi-Automatic Reconstruction of Indoors of Existing Buildings, written by Macher et al. (from IDS dated 3/11/24).
With respect to claim 2, Thomson et al. discloses the method of claim 1 above.
While Thomson et al. teaches receiving a point cloud (PC) representation of the built structure and generating a plurality of planes from the PC, Thomson et al. does not explicitly disclose “in which the PC contains a data set with a plurality of data points, one or more scan positions, a 3D coordinate value (XYZ), and a scan index value associated therewith.”
Macher et al. discloses “in which the PC contains a data set with a plurality of data points, one or more scan positions, a 3D coordinate value (XYZ), and a scan index value associated therewith.” as [Macher et al. (Pg. 6, Scan stations, “optimize the placement of scan stations in order to acquire the whole environment without causing redundant data by multiplying scan stations”, Macher et al. Pg. 7, Targets, “use at least 4 targets in common between two scans: 3 targets are sufficient to register point clouds issued from 2 successive scans but it is recommended to take more than 3 and to compensate the whole network of targets at once”, Macher et al. (Pg. 10, sec. 3.2.2 Segmentations into Planes and Point Classification, 1st paragraph, “Once room point clouds are identified, the altitudes of ceiling and floor of each room are determined. A plane segmentation is performed at these altitudes and points corresponding to ceilings and floors are extracted.”, Macher et al. Pg. 10, sec. 3.2.2 Segmentations into Planes and Point Classification, 2nd paragraph, “After removing ceilings and floors, room point clouds still contain points belonging to walls but also points belonging to occluding objects such as furniture for example desks, computer equipment, chairs and cabinets (see Figure 5a). At this stage, two assumptions are done: on one hand, points located in the borders of rooms are presumably points belonging to walls, and on the other hand, occluding
objects generally do not reach the ceilings. Thus based on both room boundaries determined during the room segmentation, and the higher part of the remaining room point cloud, top of walls are identified and then points belonging to walls can be isolated.”)];
Thomson et al. and Macher et al. are analogous art because they are from the same field endeavor of analyzing the development of a building information models from points clouds.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Thomson et al. of receiving a point cloud (PC) representation of the built structure and generating a plurality of planes from the PC by incorporating in which the PC contains a data set with a plurality of data points, one or more scan positions, a 3D coordinate value (XYZ), and a scan index value associated therewith as taught by Macher et al. for the purpose of reconstructing of the indoors of existing buildings.
Thomson et al. in view of Macher et al. teaches in which the PC contains a data set with a plurality of data points, one or more scan positions, a 3D coordinate value (XYZ), and a scan index value associated therewith.
The motivation for doing so would have been because Macher et al. teaches that by reconstructing the indoors of existing buildings the ability to analyze several datasets for the indoors of different buildings can be accomplished. This allows a way to use a default threshold in the integration from points clouds to BIM software (Macher et al. Pg. 26, sec. 6 Conclusions, 1st – 3rd paragraph, “The aim of this article was to present a processing chain conceived for the 3D semi-automatic, ETC.”).
With respect to claim 12, Thomson et al. discloses the method of claim 1 above.
While Thomson et al. teaches receiving a point cloud (PC) representation of the built structure and generating a plurality of planes from the PC, Thomson et al. does not explicitly disclose “the step of projecting the points associated with a plane to 2D and re- projecting those points back into 3D in order to form the vertices of a simple rectangular collision mesh.”
Macher et al. discloses “the step of projecting the points associated with a plane to 2D” as [Macher et al. (Pg. 4, 2nd paragraph, “Then, the remaining point cloud is projected onto the X-Y plane and planes corresponding to walls are extracted by considering room boundaries in the 2D plane. Once planes are extracted from point clouds and identified as a part of a wall, a ceiling or a ground, different modelling strategies can be carried out.”)];
“and re- projecting those points back into 3D in order to form the vertices of a simple rectangular collision mesh.” as [Macher et al. (Pg. 3, 1st paragraph, “Software dedicated to point cloud processing such as Realworks (Trimble), CloudCompare (EDF R&D) or 3D Reshaper (Technodigit) propose tools to create geometric primitives or meshes directly from 3D data.”, Macher et al. Pg. 13, sec. 3.3 Reconstruction of Structural Elements, “Planes composing walls, ceilings and floors were identified thanks to successive segmentations. These elements are still in form of point clouds. At this stage, a 3D reconstruction of the structural elements of the building (walls and slabs) must be performed. To reconstruct slabs and walls and to export the result into a BIM format, two steps are necessary. The 3D geometry of the elements is first described into the obj format [61] developed by Wavefront Technologies. This format is a simple
data-format which is open and which is used by a plenty of 3D graphics applications.”, Macher et al. Pg. 13, sec. 3.3.1 Element Description into Obj Format, 2nd paragraph, “A slab is described by a rectangular solid. In the vertical plane the level of the upper and the lower part of the slab is used and in the horizontal plane slab limits are determined considering the contours of the floor.”)];
Thomson et al. and Macher et al. are analogous art because they are from the same field endeavor of analyzing the development of a building information models from points clouds.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Thomson et al. of receiving a point cloud (PC) representation of the built structure and generating a plurality of planes from the PC by incorporating the step of projecting the points associated with a plane to 2D and re- projecting those points back into 3D in order to form the vertices of a simple rectangular collision mesh as taught by Macher et al. for the purpose of reconstructing of the indoors of existing buildings.
Thomson et al. in view of Macher et al. teaches the step of projecting the points associated with a plane to 2D and re- projecting those points back into 3D in order to form the vertices of a simple rectangular collision mesh.
The motivation for doing so would have been because Macher et al. teaches that by reconstructing the indoors of existing buildings the ability to analyze several datasets for the indoors of different buildings can be accomplished. This allows a way to use a default threshold in the integration from points clouds to BIM software (Macher et al. Pg. 26, sec. 6 Conclusions, 1st – 3rd paragraph, “The aim of this article was to present a processing chain conceived for the 3D semi-automatic, ETC.”).
Claim(s) 3-4, 8-10 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over
Thomson et al. in view of online reference Automatic reconstruction of parametric building models from indoor point clouds, written by Ochmann et al.
With respect to claim 3, Thomson et al. discloses the method of claim 1 above.
While Thomson et al. teaches receiving a point cloud (PC) representation of the built structure and generating a plurality of planes from the PC, Thomson et al. does not explicitly disclose “the intermediate step of defining an arrangement graph.”
Ochmann et al. discloses “the intermediate step of defining an arrangement graph.” as [Ochmann et al. (Pg. 96, right col., 1st paragraph, “Since our goal is to extract a piecewise-linear graph of walls, we construct a partitioning based on potential wall surfaces: we first detect vertical planes as candidates for wall surfaces and project them to the horizontal plane (Fig. 3(c)). Similar to previous approaches [9,11,12] we then construct an arrangement of (infinitely long) lines from the set of possible wall surfaces (Fig. 3(d)).”, Fig. 3(d))];
Thomson et al. and Ochmann et al. are analogous art because they are from the same field endeavor of analyzing the development of a building information models from points clouds.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Thomson et al. of receiving a point cloud (PC) representation of the built structure and generating a plurality of planes from the PC by incorporating the intermediate step of defining an arrangement graph as taught by Ochmann et al. for the purpose of reconstructing the indoors of existing buildings.
Thomson et al. in view of Ochmann et al. teaches the intermediate step of defining an arrangement graph.
The motivation for doing so would have been because Ochmann et al. teaches that by reconstructing the indoors of existing buildings, the ability to reconstruct multi-story building models at the same time can be accomplished. This allows for a more efficient way to process the multiple designs for multiple buildings (Ochmann et al. Pg. 102, sec. 9 Conclusion and Future work, “We presented the first automatic method, etc.”).
With respect to claim 4, the combination of Thomson et al. and Ochmann et al. discloses the method of claim 3 above, and Ochmann et al. further discloses “the step of generating the parametric structural design model using the arrangement graph.” as [Ochmann et al. (Pg. 96, right col., sec. 3 Approach, last paragraph, “The determination of a globally plausible labeling is then formulated as an energy minimization problem. This allows us to incorporate room layout priors and wall selection priors as unary and binary costs into one optimization. After an optimal labeling has been determined, only retaining edges separating differently labeled regions are the sought wall structures (Fig. 3(e)). Extruding walls according to estimated room heights and a detection and classification of openings yields the final parametric model (Fig. 3(f)).”, Fig. 3(f))];
With respect to claim 8, Thomson et al. discloses the method of claim 1 above.
While Thomson et al. teaches receiving a point cloud (PC) representation of the built structure and generating a plurality of planes from the PC, Thomson et al. does not explicitly disclose “the intermediate step of, after receiving the PC, subsampling the PC data points according to a three-dimension (3D) voxel grid.”
Ochmann et al. discloses “the intermediate step of, after receiving the PC, subsampling the PC data points according to a three-dimension (3D) voxel grid.” as [Ochmann et al. (Pg. 100, sec. 8 Evaluation, 1st paragraph, “We tested our approach on real-world point clouds of 14 stories from 5 different buildings; statistics are given in Table 1. The
shown number of points is after subsampling with the Point Cloud Library [14] using a resolution of ε =0:02 cm (i.e. in a voxel grid with a resolution of ε, at most one point in each voxel is retained).”, With there being a voxel grid, demonstrates that there’s a three-dimension (3D) voxel grid, since a voxel is any of the discrete elements comprising a three-dimensional entity, see attachment of definition of a voxel)];
Thomson et al. and Ochmann et al. are analogous art because they are from the same field endeavor of analyzing the development of a building information models from points clouds.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Thomson et al. of receiving a point cloud (PC) representation of the built structure and generating a plurality of planes from the PC by incorporating the intermediate step of, after receiving the PC, subsampling the PC data points according to a three-dimension (3D) voxel grid as taught by Ochmann et al. for the purpose of reconstructing the indoors of existing buildings.
Thomson et al. in view of Ochmann et al. teaches the intermediate step of, after receiving the PC, subsampling the PC data points according to a three-dimension (3D) voxel grid.
The motivation for doing so would have been because Ochmann et al. teaches that by reconstructing the indoors of existing buildings, the ability to reconstruct multi-story building models at the same time can be accomplished. This allows for a more efficient way to process the multiple designs for multiple buildings (Ochmann et al. Pg. 102, sec. 9 Conclusion and Future work, “We presented the first automatic method, etc.”).
With respect to claim 9, the combination of Thomson et al. and Ochmann et al. discloses the method of claim 8 above, and Ochmann et al. further discloses “applying a normal estimation function across the subsampled PC data points” as [Ochmann et al. (Pg. 100, sec. 8 Evaluation, 1st paragraph, “We tested our approach on real-world point clouds of 14 stories from 5 different buildings; statistics are given in Table 1. The shown number of points is after subsampling with the Point Cloud Library [14] using a resolution of ε =0:02 cm (i.e. in a voxel grid with a resolution of ε, at most one point in each voxel is retained). Normals are estimated by means of local PCA using point patches of 48 nearest neighbors. Normals are flipped towards the respective scanner position.”)];
“and, assigning a 3D normal vector to each data point in addition to their 3D Cartesian coordinate.” as [Ochmann et al. (Pg. 97, sec. 5 Generation of wall candidates, 2nd paragraph, “Nearly vertical planes ð711Þ with a sufficiently large approximate area ð⩾1:5 m2Þ
are considered as potential wall surfaces. For a plane P fulfilling these constraints, let nP ε R3 be the plane normal and PP the set of measured points supporting P. Each extracted plane P is transferred to the horizontal plane as a wall surface line lP defined by 〈nlP ; x〉_dlP =0. A schematic example for the extraction of wall surface lines is shown in Fig. 4(a)–(c).”, Fig. 4(c))];
With respect to claim 10, the combination of Thomson et al. and Ochmann et al. discloses the method of claim 9 above, and Ochmann et al. further discloses “the step of planar object recognition including: defining each planar object as the equation of its plane” as [Ochmann et al. (Pg. 97, sec. 5 Generation of wall candidates, 2nd paragraph, “Nearly vertical planes ð711Þ with a sufficiently large approximate area ð⩾1:5 m2Þ are considered as potential wall surfaces. For a plane P fulfilling these constraints, let nP ε R3 be the plane normal and PP the set of measured points supporting P. Each extracted plane P is transferred to the horizontal plane as a wall surface line lP defined by 〈nlP ; x〉_dlP =0. A schematic example for the extraction of wall surface lines is shown in Fig. 4(a)–(c).”)];
“a surface normal vector” as [Ochmann et al. (Pg. 97, sec. 5 Generation of wall candidates, 2nd paragraph, “Nearly vertical planes ð711Þ with a sufficiently large approximate area ð⩾1:5 m2Þ are considered as potential wall surfaces. For a plane P fulfilling these constraints, let nP ε R3 be the plane normal and PP the set of measured points supporting P. Each extracted plane P is transferred to the horizontal plane as a wall surface line lP defined by 〈nlP ; x〉_dlP =0. A schematic example for the extraction of wall surface lines is shown in Fig. 4(a)–(c).”, Fig. 4(c), lp1 and lp2 are perpendicular to the wall surface line lp, which demonstrates that there’s a surface normal vector)];
“and the set of data points that lie on its plane.” as [Ochmann et al. (Pg. 99, sec. 7 Model generation and opening detection, middle of 2nd paragraph, “For each plane, the number of support points located within f is determined. The elevation of the plane with the largest support within f and upwards- (resp. downwards-) facing normal is chosen as the floor height hfl(f) (resp. ceiling height hd(f)) of f.”, The examiner considers the support points to be the data points, since the support points are located on the plane)];
With respect to claim 13, Thomson et al. discloses the method of claim 1 above.
While Thomson et al. teaches receiving a point cloud (PC) representation of the built structure and generating a plurality of planes from the PC, Thomson et al. does not explicitly disclose “the step of collapsing all the data points into a 2D array and applying a Gaussian smoothing technique to the 2D array.”
Ochmann et al. discloses “the step of collapsing all the data points into a 2D array and applying a Gaussian smoothing technique to the 2D array.” as [Ochmann et al. (Pg. 100, sec. 8 Evaluation, bottom of 2nd paragraph “We also found that smoothing the 2D and 1D grids used for the determination of face and edge label vectors in Section 6 using a large Gaussian kernel usually improves results.”)];
Thomson et al. and Ochmann et al. are analogous art because they are from the same field endeavor of analyzing the development of a building information models from points clouds.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Thomson et al. of receiving a point cloud (PC) representation of the built structure and generating a plurality of planes from the PC by incorporating the step of collapsing all the data points into a 2D array and applying a Gaussian smoothing technique to the 2D array as taught by Ochmann et al. for the purpose of reconstructing the indoors of existing buildings.
Thomson et al. in view of Ochmann et al. teaches the step of collapsing all the data points into a 2D array and applying a Gaussian smoothing technique to the 2D array.
The motivation for doing so would have been because Ochmann et al. teaches that by reconstructing the indoors of existing buildings, the ability to reconstruct multi-story building models at the same time can be accomplished. This allows for a more efficient way to process the multiple designs for multiple buildings (Ochmann et al. Pg. 102, sec. 9 Conclusion and Future work, “We presented the first automatic method, etc.”).
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over
Thomson et al. in view of Ochmann et al. in further view of online reference From Point Clouds to Building Information Models: 3D Semi-Automatic Reconstruction of Indoors of Existing Buildings, written by Macher et al. (from IDS dated 3/11/24).
With respect to claim 11, the combination of Thomson et al. and Ochmann et al. discloses the method of claim 10 above, and Ochmann et al. further discloses “defining a projection function from 3D to two dimension (2D) so that a data point may be mapped from 3D onto a flat 2D surface” as [Ochmann et al. (Pg. 95 sec. 2, 1st paragraph, “Okorn et al. [13] generate 2D floor plans from 3D point clouds. A histogram of the vertical positions of all measured points is built. Peaks in this histogram are considered to be large horizontal planar structures (i.e. floor and ceiling surfaces).”)];
While the combination of Thomson et al. and Ochmann et al. teaches defining a projection function from 3D to two dimension (2D) so that a data point may be mapped from 3D onto a flat 2D surface, Thomson et al. and Ochmann et al. do not explicitly disclose “and defining a reprojection function from 2D to 3D so that the point may be mapped from a 2D plane into 3D space.”
Macher et al. discloses “and defining a reprojection function from 2D to 3D so that the point may be mapped from a 2D plane into 3D space.” as [Macher et al. (Pg. 9, 4th paragraph, “Finally, to move from 2D to 3D regions representing the rooms, 2D regions are considered from ground height to ceiling height of the floor. A filter is also considered to eliminate 3D regions which are too small or which do not describe rooms.”)];
Thomson et al., Ochmann et al. and Macher et al. are analogous art because they are from the same field endeavor of analyzing the development of a building information models from points clouds.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Thomson et al. and Ochmann et al. of defining a projection function from 3D to two dimension (2D) so that a data point may be mapped from 3D onto a flat 2D surface by incorporating and defining a reprojection function from 2D to 3D so that the point may be mapped from a 2D plane into 3D space as taught by Macher et al. for the purpose of reconstructing of the indoors of existing buildings.
Thomson et al. in view of Ochmann et al. in further view of Macher et al. teaches and defining a reprojection function from 2D to 3D so that the point may be mapped from a 2D plane into 3D space.
The motivation for doing so would have been because Macher et al. teaches that by reconstructing the indoors of existing buildings the ability to analyze several datasets for the indoors of different buildings can be accomplished. This allows a way to use a default threshold in the integration from points clouds to BIM software (Macher et al. Pg. 26, sec. 6 Conclusions, 1st – 3rd paragraph, “The aim of this article was to present a processing chain conceived for the 3D semi-automatic, ETC.”).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The relevance of online reference Automated Semantic Labelling of 3D Vector Models for Scan-to-BIM, written by Bassier et al. teaches labeling highly cluttered vector models of existing buildings.
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/BERNARD E COTHRAN/Examiner, Art Unit 2188
/RYAN F PITARO/Supervisory Patent Examiner, Art Unit 2188