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 Preliminary Amendment
The preliminary amendment filed on January 21, 2025 has been entered.
In view of the amendment to the claims, claim 1 has been canceled and new claims 2-21 have been added.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
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Claims 2, 7-9 and 14-15 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-3 and 11-13 of Patent No. 12,243,163 B2. Although the conflicting claims are not identical, they are not patentably distinct from each other because: the instant claims are substantially similar to the claims in the conflicting patent, as shown in the following tables.
Claim 2 is rejected for obviousness-type double patenting under claim 1 of Patent No. 12,243,163 B2
Instant application claim 2
Claim 1 of Patent No. 12,243,163
A method of implemented by a system of one or more computers, the method comprising:
A method implemented by a system of one or more computers, the method comprising:
providing access to an image depicting a structure, the structure having a plurality of planar elements comprising at least a roof facet and one or more walls;
providing access to an image depicting a structure, the image being captured via a user device positioned proximate to the structure, the structure having a plurality of planar elements comprising at least a roof facet and one or more walls;
providing the image as input to a neural network, wherein the neural network outputs, at least, a surface normal associated with the roof facet and a surface normal associated with a particular wall of the one or more walls;
providing the image as input to a neural network, wherein the neural network outputs, at least, a surface normal associated with the roof facet and a surface normal associated with a particular wall of the one or more walls;
adjusting each surface normal based on a transform, wherein the transform adjusts at least the surface normal associated with the particular wall to be substantially orthogonal to a vertical orientation; and
adjusting each surface normal based on a transform, wherein the transform adjusts at least the surface normal associated with the particular wall to be substantially orthogonal to a vertical orientation; and
extracting a pitch of the roof facet based on the adjusted surface normal associated with the roof facet and a vertical vector.
extracting a pitch of the roof facet based on the adjusted surface normal associated with the roof facet and a gravity vector.
Claim 7 is rejected for obviousness-type double patenting under claim 2 of Patent No. 12,243,163 B2
Instant application claim 7
Claim 2 of Patent No. 12,243,163
The method of claim 2, wherein the neural network comprises a convolutional neural network trained to segment the planar elements into at least the roof facet or the one or more walls.
The method of claim 1, wherein the neural network comprises a convolutional neural network trained to segment the planar elements into at least the roof facet or the wall.
Claim 8 is rejected for obviousness-type double patenting under claim 3 of Patent No. 12,243,163 B2
Instant application claim 8
Claim 3 of Patent No. 12,243,163
The method of claim 7, wherein the neural network further comprises one or more fully-connected layers which receive output from the convolutional neural network, and wherein the fully-connected layers are trained to output individual surface normals associated with individual planar elements.
The method of claim 2, wherein the neural network further comprises one or more fully-connected layers which receive output from the convolutional neural network, and wherein the fully-connected layers are trained to output individual surface normals associated with individual planar elements.
Claim 9 is rejected for obviousness-type double patenting under claim 11 of Patent No. 12,243,163 B2
Instant application claim 9
Claim 11 of Patent No. 12,243,163
A system comprising one or more processors and non-transitory computer readable media storing instructions which, when executed by the one or more processors, cause the one or more processors to:
A system comprising one or more processors and non-transitory computer readable media storing instructions which, when executed by the one or more processors, cause the one or more processors to:
provide access to an image depicting a structure, the structure having a plurality of planar elements comprising at least a roof facet and one or more walls;
provide access to an image depicting a structure, the image being captured via a user device positioned proximate to the structure, the structure having a plurality of planar elements comprising at least a roof facet and one or more walls;
provide the image as input to a neural network, wherein the neural network outputs, at least, a surface normal associated with the roof facet and a surface normal associated with a particular wall of the one or more walls;
provide the image as input to a neural network, wherein the neural network outputs, at least, a surface normal associated with the roof facet and a surface normal associated with a particular wall of the one or more walls;
adjust each surface normal based on a transform, wherein the transform adjusts at least the surface normal associated with the particular wall to be substantially orthogonal to a vertical orientation; and
adjust each surface normal based on a transform, wherein the transform adjusts at least the surface normal associated with the particular wall to be substantially orthogonal to a vertical orientation; and
extract a pitch of the roof facet based on the adjusted surface normal associated with the roof facet and a vertical vector.
extracting a pitch of the roof facet based on the adjusted surface normal associated with the roof facet and a gravity vector.
Claim 14 is rejected for obviousness-type double patenting under claim 12 of Patent No. 12,243,163 B2
Instant application claim 14
Claim 12 of Patent No. 12,243,163
The system of claim 9, wherein the neural network comprises a convolutional neural network trained to segment the planar elements into at least the roof facet or the one or more walls.
The system of claim 11, wherein the neural network comprises a convolutional neural network trained to segment the planar elements into at least the roof facet or the wall.
Claim 15 is rejected for obviousness-type double patenting under claim 13 of Patent No. 12,243,163 B2
Instant application claim 15
Claim 13 of Patent No. 12,243,163
The system of claim 14, wherein the neural network further comprises one or more fully-connected layers which receive output from the convolutional neural network, and wherein the fully-connected layers are trained to output individual surface normals associated with individual planar elements.
The system of claim 12, wherein the neural network further comprises one or more fully-connected layers which receive output from the convolutional neural network, and wherein the fully-connected layers are trained to output individual surface normals associated with individual planar elements.
Claims 16 and 20-21 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 11-13 of Patent No. 12,243,163 B2. Although the conflicting claims are not identical, they are not patentably distinct from each other because:
Here is the general claim correspondence between the inventions, as shown in the following tables.
Claim 16 is rejected for obviousness-type double patenting under claim 1 of Patent No. 12,243,163 B2
Instant application claim 16
Claim 11 of Patent No. 12,243,163
Non-transitory computer storage media storing instructions that when executed by a system of one or more processors, cause the one or more processors to perform operations comprising:
A system comprising one or more processors and non-transitory computer readable media storing instructions which, when executed by the one or more processors, cause the one or more processors to:
providing access to an image depicting a structure, the structure having a plurality of planar elements comprising at least a roof facet and one or more walls;
provide access to an image depicting a structure, the image being captured via a user device positioned proximate to the structure, the structure having a plurality of planar elements comprising at least a roof facet and one or more walls;
providing the image as input to a neural network, wherein the neural network outputs, at least, a surface normal associated with the roof facet and a surface normal associated with a particular wall of the one or more walls;
provide the image as input to a neural network, wherein the neural network outputs, at least, a surface normal associated with the roof facet and a surface normal associated with a particular wall of the one or more walls;
adjusting each surface normal based on a transform, wherein the transform adjusts at least the surface normal associated with the particular wall to be substantially orthogonal to a vertical orientation; and
adjust each surface normal based on a transform, wherein the transform adjusts at least the surface normal associated with the particular wall to be substantially orthogonal to a vertical orientation; and
extracting a pitch of the roof facet based on the adjusted surface normal associated with the roof facet and a vertical vector.
extracting a pitch of the roof facet based on the adjusted surface normal associated with the roof facet and a gravity vector.
Claim 20 is rejected for obviousness-type double patenting under claim 2 of Patent No. 12,243,163 B2
Instant application claim 20
Claim 12 of Patent No. 12,243,163
The non-transitory computer storage media of claim 16, wherein the neural network comprises a convolutional neural network trained to segment the planar elements into at least the roof facet or the one or more walls.
The system of claim 11, wherein the neural network comprises a convolutional neural network trained to segment the planar elements into at least the roof facet or the wall.
Claim 21 is rejected for obviousness-type double patenting under claim 13 of Patent No. 12,243,163 B2
Instant application claim 21
Claim 13 of Patent No. 12,243,163
The non-transitory computer storage media of claim 20, wherein the neural network further comprises one or more fully-connected layers which receive output from the convolutional neural network, and wherein the fully-connected layers are trained to output individual surface normals associated with individual planar elements.
The system of claim 12, wherein the neural network further comprises one or more fully-connected layers which receive output from the convolutional neural network, and wherein the fully-connected layers are trained to output individual surface normals associated with individual planar elements.
As shown in the tables above, all the claimed features from claims 16 and 20-21 in the instant application are taught in claims 11-13 in US Patent 12,243,163 with the exception of the claim being non-transitory computer storage media storing instructions that when executed by a system of one or more processors, cause the one or more processors to perform operations. However, these features would have been obvious to incorporated into claims 11-13 in US Patent 12,243,163 in order to provide a non-transitory computer storage media storing instructions and perform the operations on a computer-based device.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2-21 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Independent claims 2, 9 and 16 recites “... providing/provide the image as input to a neural network, wherein the neural network outputs, at least, a surface normal associated with the roof facet and a surface normal associated with a particular wall of the one or more walls ...”. The claim uses “a surface normal” to associate with “the roof facet” and “a particular wall”. The issue is persons of ordinary skill in the art reading the specification is not able to understand how to distinguish between two of “a surface normal”. Therefore, the examiner deems the claims indefinite as they fail to particularly point out and distinctly claim what Applicant regards as the invention. Accordingly, the claims are rejected under U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph.
Dependent claims 3-8 depend upon independent claim 2; dependent claims 10-15 depend upon independent claim 9; Dependent claims 17-21 depend upon independent claim 16. They are rejected at least due to their respective dependencies from a rejected claim.
Examiner’s Comment
Claims 2-21 have not art rejection but rejected under double patenting and U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph. A final determination of patentability, after further search, will be mode upon resolution of above double patenting and 35 U.S.C. 112 rejection.
The examiner has completed the prior art reference search and discovered the closest prior art references:
The prior art reference WALTMAN et al (US/ Patent Application Publication 2021/0279811 A1) discloses a system configured for generating an inspection report utilizing a machine learning model (As shown in FIG. 1). More specifically, the system receives images and videos captured by the homeowner of their home's interior and exterior; determines roof slopes using plane segmentation and surface normal estimation algorithms to identify as hazardous if the roof slope is too steep or too shallow; estimates the risk assessment score of the collective property; then generate an inspection report.
The prior art reference Yeh et al (US/ Patent Application Publication 2020/0057824 A1) discloses techniques for using a computation engine executing a machine learning system to generate, according to constraints, renderings of a building or building information modeling (BIM) data for the building. More specifically, the system receives surfaces for a building and building constraints including an architectural style; applies surfaces for a building and building constraints to generate a rendering of the surfaces according to the selected building constraints; outputs the rendering of the surfaces; then applies a BIM generation model to generate BIM data for the image of the one or more surfaces according to one or more constraints in the at least one of the architectural style (As shown in FIG. 6).
The prior art reference Porter et al (US/ Patent Application Publication 2019/0385363 A1) discloses a system and a method for modeling a roof of a structure. More specifically, the method performs an imagery selection phase (retrieves images and metadata based on a geospatial region of interest); performs a neural network inference phase to produce 2D outputs in pixel space, such as surface gradients, line gradients, line types, corners, etc., for one or more structures in the retrieved image(s); performs a line extraction selection phase to create 2D line segment geometries in the pixel space; performs a line graph construction phase to group segments into directed contour graphs of various heights; performs a 3D reconstruction phase by transforming the line data into 3D line segment geometries in world space (As shown in FIG. 2).
The prior art reference Upendran et al (US/ Patent Application Publication 2019/0371057 A1) discloses a system and method for creating multi-dimensional building models based on a series of captured building images. More specifically, the method initiates a capture device for a specific building; receives the captured ground level image of building and upload to image processing servers to create a 3D model (As shown in FIG. 2).
The prior art reference Moreno et al (US/ Patent Application Publication 2019/0279420 A1) discloses systems and methods for automatically generating a 3D model of a roof of a building. More specifically, the method receives point cloud data including a plurality of data points corresponding to height measurements of a building at a given location; processes the point cloud data to identify roof surfaces; generates a 3D model of the roof using the identified surfaces; receives aerial imagery of the roof; registers the aerial imagery with the point cloud data; refines the 3D model using the aerial imagery data; measures the 3D model to obtain measurements of the roof (As shown in FIG. 2).
The prior art reference Milbert et al (US/ Patent Application Publication 2019/0088032 A1) discloses a method for generating roof reports. More specifically, the method receives a request of a roof report for a given structure; prepare a 3D model for the specified structure by extracting a roof model; inspects the roof model and request corrections; generates a roof report based on the roof model (As shown in FIG. 2).
The prior art reference Hirzer et al (US/ Patent Application Publication 2019/0080467 A1) discloses a system receives an image of an urban scene from the image capture device and rectifies the image; determines the angles between vertical edges in the input image and the local vertical direction; uses the angles to rectify the input image, so that the vertical edges of the image are aligned in the same direction as corresponding vertical lines in the 3D rendering (As shown in FIGS. 3A and 3B).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Xilin Guo whose telephone number is (571)272-5786. The examiner can normally be reached Monday - Friday 9:00 AM-5:30 PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Daniel Hajnik can be reached at 571-272-7642. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/XILIN GUO/Primary Examiner, Art Unit 2616
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