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公开(公告)号：US12073609B2
公开(公告)日：2024-08-27
申请号：US18302780
申请日：2023-04-18
申请人： Matterport, Inc.
发明人： Gunnar Hovden , Mykhaylo Kurinnyy
IPC分类号： G06V10/778 , G06F18/21 , G06T15/04 , G06T15/20 , G06T17/00 , G06T19/00 , G06V20/00 , G06V20/10 , G06V20/64
CPC分类号： G06V10/7796 , G06F18/2193 , G06T15/04 , G06T15/205 , G06T17/00 , G06T19/003 , G06V20/10 , G06V20/35 , G06T2210/04 , G06V20/647
摘要： Techniques are provided for increasing the accuracy of automated classifications produced by a machine learning engine. Specifically, the classification produced by a machine learning engine for one photo-realistic image is adjusted based on the classifications produced by the machine learning engine for other photo-realistic images that correspond to the same portion of a 3D model that has been generated based on the photo-realistic images. Techniques are also provided for using the classifications of the photo-realistic images that were used to create a 3D model to automatically classify portions of the 3D model. The classifications assigned to the various portions of the 3D model in this manner may also be used as a factor for automatically segmenting the 3D model.
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公开(公告)号：US20230290072A1
公开(公告)日：2023-09-14
申请号：US18182247
申请日：2023-03-10
申请人： Matterport, Inc.
发明人： Gunnar Hovden , Azwad Sabik
IPC分类号： G06T19/00 , G06V10/82 , G06T7/70 , G06V10/764
CPC分类号： G06T19/003 , G06V10/82 , G06T7/70 , G06V10/764 , G06T2207/20084 , G06T2207/30244 , G06T2207/10028 , G06T2219/004
摘要： A system comprising: processors and memory containing instructions to control processors to: receive images representing an interior of a physical environment, identify, using neural network for object recognition, an object in an image, the object is associated with a location relative to the physical environment, identify, using neural network for object recognition, another object in another image, determine if objects in the images are located near or at a similar location based on location information associated with the objects, if the objects are located near or at a similar location, then objects are an instance of a single object, store similar location associated with the single object, display an interactive walkthrough visualization of a 3D model of the physical environment including the single object, receive request regarding object location through the interactive walkthrough visualization, and provide the similar location of the single object for display in the interactive walkthrough visualization.
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公开(公告)号：US20230260265A1
公开(公告)日：2023-08-17
申请号：US18302780
申请日：2023-04-18
申请人： Matterport, Inc.
发明人： Gunnar Hovden , Mykhaylo Kurinnyy
IPC分类号： G06V10/778 , G06T15/20 , G06T15/04 , G06T19/00 , G06T17/00 , G06V20/00 , G06V20/10 , G06F18/21
CPC分类号： G06V10/7796 , G06T15/205 , G06T15/04 , G06T19/003 , G06T17/00 , G06V20/35 , G06V20/10 , G06F18/2193 , G06T2210/04 , G06V20/647
摘要： Techniques are provided for increasing the accuracy of automated classifications produced by a machine learning engine. Specifically, the classification produced by a machine learning engine for one photo-realistic image is adjusted based on the classifications produced by the machine learning engine for other photo-realistic images that correspond to the same portion of a 3D model that has been generated based on the photo-realistic images. Techniques are also provided for using the classifications of the photo-realistic images that were used to create a 3D model to automatically classify portions of the 3D model. The classifications assigned to the various portions of the 3D model in this manner may also be used as a factor for automatically segmenting the 3D model.
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公开(公告)号：US20210374410A1
公开(公告)日：2021-12-02
申请号：US17235815
申请日：2021-04-20
申请人： Matterport, Inc.
发明人： Gunnar Hovden , Mykhaylo Kurinnyy
摘要： Techniques are provided for increasing the accuracy of automated classifications produced by a machine learning engine. Specifically, the classification produced by a machine learning engine for one photo-realistic image is adjusted based on the classifications produced by the machine learning engine for other photo-realistic images that correspond to the same portion of a 3D model that has been generated based on the photo-realistic images. Techniques are also provided for using the classifications of the photo-realistic images that were used to create a 3D model to automatically classify portions of the 3D model. The classifications assigned to the various portions of the 3D model in this manner may also be used as a factor for automatically segmenting the 3D model.
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公开(公告)号：US10984244B2
公开(公告)日：2021-04-20
申请号：US16742845
申请日：2020-01-14
申请人： Matterport, Inc.
发明人： Gunnar Hovden , Mykhaylo Kurinnyy
摘要： Techniques are provided for increasing the accuracy of automated classifications produced by a machine learning engine. Specifically, the classification produced by a machine learning engine for one photo-realistic image is adjusted based on the classifications produced by the machine learning engine for other photo-realistic images that correspond to the same portion of a 3D model that has been generated based on the photo-realistic images. Techniques are also provided for using the classifications of the photo-realistic images that were used to create a 3D model to automatically classify portions of the 3D model. The classifications assigned to the various portions of the 3D model in this manner may also be used as a factor for automatically segmenting the 3D model.
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公开(公告)号：US10534962B2
公开(公告)日：2020-01-14
申请号：US15626104
申请日：2017-06-17
申请人： Matterport, Inc.
发明人： Gunnar Hovden , Mykhaylo Kurinnyy , Matthew Bell
摘要： Techniques are provided for increasing the accuracy of automated classifications produced by a machine learning engine. Specifically, the classification produced by a machine learning engine for one photo-realistic image is adjusted based on the classifications produced by the machine learning engine for other photo-realistic images that correspond to the same portion of a 3D model that has been generated based on the photo-realistic images. Techniques are also provided for using the classifications of the photo-realistic images that were used to create a 3D model to automatically classify portions of the 3D model. The classifications assigned to the various portions of the 3D model in this manner may also be used as a factor for automatically segmenting the 3D model.
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公开(公告)号：US20180365496A1
公开(公告)日：2018-12-20
申请号：US15626104
申请日：2017-06-17
申请人： Matterport, Inc.
发明人： Gunnar Hovden , Mykhaylo Kurinnyy , Matthew Bell
CPC分类号： G06K9/00684 , G06K9/00208 , G06K9/00664 , G06K9/6265 , G06T15/04 , G06T15/205 , G06T17/00 , G06T19/003 , G06T2210/04
摘要： Techniques are provided for increasing the accuracy of automated classifications produced by a machine learning engine. Specifically, the classification produced by a machine learning engine for one photo-realistic image is adjusted based on the classifications produced by the machine learning engine for other photo-realistic images that correspond to the same portion of a 3D model that has been generated based on the photo-realistic images. Techniques are also provided for using the classifications of the photo-realistic images that were used to create a 3D model to automatically classify portions of the 3D model. The classifications assigned to the various portions of the 3D model in this manner may also be used as a factor for automatically segmenting the 3D model.
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公开(公告)号：US11670076B2
公开(公告)日：2023-06-06
申请号：US17235815
申请日：2021-04-20
申请人： Matterport, Inc.
发明人： Gunnar Hovden , Mykhaylo Kurinnyy
IPC分类号： G06V20/00 , G06T15/20 , G06T15/04 , G06T19/00 , G06T17/00 , G06K9/62 , G06V20/10 , G06V20/64
CPC分类号： G06V20/35 , G06K9/6265 , G06T15/04 , G06T15/205 , G06T17/00 , G06T19/003 , G06V20/10 , G06T2210/04 , G06V20/647
摘要： Techniques are provided for increasing the accuracy of automated classifications produced by a machine learning engine. Specifically, the classification produced by a machine learning engine for one photo-realistic image is adjusted based on the classifications produced by the machine learning engine for other photo-realistic images that correspond to the same portion of a 3D model that has been generated based on the photo-realistic images. Techniques are also provided for using the classifications of the photo-realistic images that were used to create a 3D model to automatically classify portions of the 3D model. The classifications assigned to the various portions of the 3D model in this manner may also be used as a factor for automatically segmenting the 3D model.
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公开(公告)号：US10706615B2
公开(公告)日：2020-07-07
申请号：US14962867
申请日：2015-12-08
申请人： Matterport, Inc.
摘要： Systems and techniques for determining and/or generating data for an architectural opening area associated with a three-dimensional (3D) model are presented. A portion of an image associated with a 3D model that corresponds to a window view or another architectural opening area is identified based at least in part on color data or depth data. Furthermore, a surface associated with the 3D model and visual data for the window view or the other architectural opening area is determined. The visual data for the window view or the other architectural opening area is applied to the surface associated with the 3D model.
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公开(公告)号：US20200151454A1
公开(公告)日：2020-05-14
申请号：US16742845
申请日：2020-01-14
申请人： Matterport, Inc.
发明人： Gunnar Hovden , Mykhaylo Kurinnyy
摘要： Techniques are provided for increasing the accuracy of automated classifications produced by a machine learning engine. Specifically, the classification produced by a machine learning engine for one photo-realistic image is adjusted based on the classifications produced by the machine learning engine for other photo-realistic images that correspond to the same portion of a 3D model that has been generated based on the photo-realistic images. Techniques are also provided for using the classifications of the photo-realistic images that were used to create a 3D model to automatically classify portions of the 3D model. The classifications assigned to the various portions of the 3D model in this manner may also be used as a factor for automatically segmenting the 3D model.
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