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公开(公告)号：US20210358051A1
公开(公告)日：2021-11-18
申请号：US17388907
申请日：2021-07-29
Inventor： Bryan R. Nussbaum , Jeremy Carnahan , John A. Schirano , Vicki King , Mike McGraw
Abstract: Methods, systems, and computer readable media for predictively determining a risk of damage to a property are provided. To determine the risk, a high resolution virtual model of a region that includes the property is obtained. The virtual model is imported into a simulation environment. One or more of the simulation parameters are set based on historic weather data for the region. For example, each parameter may be associated with a probability distribution derived based on the historic weather data that is sampled prior to executing the simulation. One or more simulations are executed in accordance with the sampled inputs to simulate the likely weather patterns the property will experience. The result of the simulation is analyzed to determine the predicted risk of damage to the property.
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公开(公告)号：US20240249473A1
公开(公告)日：2024-07-25
申请号：US18601219
申请日：2024-03-11
Inventor： Jeremy Carnahan , Michael Stine McGraw , John Andrew Schirano
IPC: G06T17/05 , G01C11/06 , G06F16/29 , G06T7/55 , G06T7/70 , G06V10/44 , G06V10/764 , G06V20/13 , G06V20/17 , G06V20/56
CPC classification number: G06T17/05 , G01C11/06 , G06F16/29 , G06T7/55 , G06T7/70 , G06V10/454 , G06V10/764 , G06V20/13 , G06V20/17 , G06V20/56 , G06V20/588 , G06T2207/10028 , G06T2207/30256
Abstract: A feature mapping computer system configured to (i) receive a localized image including a photo depicting a driving environment and location data associated with the photo, (ii) identify, using an image recognition module, a roadway feature depicted in the photo, (iii) generate, using a photogrammetry module, a point cloud based upon the photo and the location data, wherein the point cloud comprises a set of data points representing the driving environment in a three dimensional (“3D”) space, (iv) localize the point cloud by assigning a location to the point cloud based upon the location data, and (v) generate an enhanced base map that includes a roadway feature.
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公开(公告)号：US11983817B2
公开(公告)日：2024-05-14
申请号：US17543105
申请日：2021-12-06
Inventor： Bryan Nussbaum , Jeremy Carnahan , Ryan Knuffman
CPC classification number: G06T17/205 , G06F16/5866 , G06T19/006 , G06V20/20 , H04W4/021
Abstract: A computer-implemented method for labeling a three-dimensional (3D) model using virtual reality (VR) techniques implemented by a computer system including a processor is provided herein. The method may include (i) receiving a 3D model including an environmental feature that is unlabeled, (ii) displaying, through a VR device in communication with the processor, a VR environment to a user representing the 3D model, (iii) prompting a user to input labeling data for the environmental feature displayed within the VR environment of the VR device by prompting the user to select the environmental feature through user interaction with the VR device, and input labeling data for the environmental feature, wherein the labeling data identifies the environmental feature, and (iv) generating a labeled 3D model by embedding the labeling data associated with the selected environmental feature into the 3D model.
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Patent Agency Ranking
14.发明公开公开(公告)号：US20230360244A1
公开(公告)日：2023-11-09
申请号：US18355336
申请日：2023-07-19
Inventor： Ryan Knuffman , Jeremy Carnahan
CPC classification number: G06T7/579 , G06T15/205 , G06T2207/10032 , G06T2207/20084 , G06T2207/20081
Abstract: A server includes a processor and a memory storing instructions that, when executed by the processor, cause the server to receive two-dimensional (2D) images, analyze the images using a trained deep network to generate points, process the labeled points to identify tie points, and combine the 2D dimensional images into a three-dimensional (3D) point cloud using structure-from-motion. A method for generating a semantically-segmented 3D point cloud from 2D data includes receiving 2D images, analyzing the images using a trained deep network to generate labeled points, processing the points to identify tie points, and combining the 2D images into a 3D point cloud using structure-from-motion. A non-transitory computer readable storage medium stores executable instructions that, when executed by a processor, cause a computer to receive 2D images, analyze the images using a trained deep network to generate labeled points, process the points to identify and combine tie points using structure-from-motion.
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15.发明授权公开(公告)号：US11748901B1
公开(公告)日：2023-09-05
申请号：US17031643
申请日：2020-09-24
Inventor： Ryan Knuffman , Jeremy Carnahan
CPC classification number: G06T7/579 , G06T15/205 , G06T2207/10032 , G06T2207/20081 , G06T2207/20084
Abstract: A server includes a processor and a memory storing instructions that, when executed by the processor, cause the server to receive two-dimensional (2D) images, analyze the images using a trained deep network to generate points, process the labeled points to identify tie points, and combine the 2D dimensional images into a three-dimensional (3D) point cloud using structure-from-motion. A method for generating a semantically-segmented 3D point cloud from 2D data includes receiving 2D images, analyzing the images using a trained deep network to generate labeled points, processing the points to identify tie points, and combining the 2D images into a 3D point cloud using structure-from-motion. A non-transitory computer readable storage medium stores executable instructions that, when executed by a processor, cause a computer to receive 2D images, analyze the images using a trained deep network to generate labeled points, process the points to identify and combine tie points using structure-from-motion.
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公开(公告)号：US11210851B1
公开(公告)日：2021-12-28
申请号：US16543127
申请日：2019-08-16
Inventor： Bryan Nussbaum , Jeremy Carnahan , Ryan Knuffman
Abstract: A virtual reality (VR) labeling computer system configured to receive a 3D model, process the 3D model using object recognition, identify at least one environmental feature within the 3D model, generate a processed 3D model including the at least one environmental feature, display a VR environment based upon the processed 3D model; receive user input including labeling data associated with the environmental feature; generate a labeled 3D model by embedding the labeling data into the processed 3D model; and generate training data based upon the labeled 3D model.
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公开(公告)号：US11107162B1
公开(公告)日：2021-08-31
申请号：US16244923
申请日：2019-01-10
Inventor： Bryan R. Nussbaum , Jeremy Carnahan , John A. Schirano , Vicki King , Mike McGraw
Abstract: Methods, systems, and computer readable media for predictively determining a risk of damage to a property are provided. To determine the risk, a high resolution virtual model of a region that includes the property is obtained. The virtual model is imported into a simulation environment. One or more of the simulation parameters are set based on historic weather data for the region. For example, each parameter may be associated with a probability distribution derived based on the historic weather data that is sampled prior to executing the simulation. One or more simulations are executed in accordance with the sampled inputs to simulate the likely weather patterns the property will experience. The result of the simulation is analyzed to determine the predicted risk of damage to the property.
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公开(公告)号：US10410291B1
公开(公告)日：2019-09-10
申请号：US15482300
申请日：2017-04-07
Inventor： Todd Binion , Jennifer Criswell Kellett , Jeremy Carnahan , Matt Megyese
Abstract: A system for determining drone operation rules configured to (i) receive a plurality of telematics data from a plurality of missions; (ii) analyze the plurality of telematics data to determine one or more mission trends; and (iii) determine one or more rules based upon the one or more mission trends.
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