Patents by Inventor Mykhaylo Kurinnyy

Mykhaylo Kurinnyy has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20210374410
    Abstract: 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.
    Type: Application
    Filed: April 20, 2021
    Publication date: December 2, 2021
    Applicant: Matterport, Inc.
    Inventors: Gunnar Hovden, Mykhaylo Kurinnyy
  • Patent number: 11164337
    Abstract: This document describes techniques and systems that enable autocalibration for multiple cameras using near-infrared (NIR) illuminators. The techniques and systems include a user device that uses NIR images, including dot images and flood images, captured by the multiple cameras. The user device implements an autocalibration module that normalizes the contrast of each image. Then, the autocalibration module detects dot features in the dot images and detects flood features in the flood images. The autocalibration module uses the flood features to disambiguate the dot features in the dot images. Then, the autocalibration module uses the disambiguated dot features to determine new calibration parameters for recalibration of the multiple cameras. In some aspects, the autocalibration module uses the dot images, rather than the flood images, to detect the flood features for disambiguating the dot features.
    Type: Grant
    Filed: October 4, 2019
    Date of Patent: November 2, 2021
    Assignee: Google LLC
    Inventors: Edward T. Chang, Mykhaylo Kurinnyy, Zhaowei Wang, Jonathan James Taylor
  • Publication number: 20210248782
    Abstract: This document describes techniques and systems that enable autocalibration for multiple cameras using near-infrared (NIR) illuminators. The techniques and systems include a user device that uses NIR images, including dot images and flood images, captured by the multiple cameras. The user device implements an autocalibration module that normalizes the contrast of each image. Then, the autocalibration module detects dot features in the dot images and detects flood features in the flood images. The autocalibration module uses the flood features to disambiguate the dot features in the dot images. Then, the autocalibration module uses the disambiguated dot features to determine new calibration parameters for recalibration of the multiple cameras. In some aspects, the autocalibration module uses the dot images, rather than the flood images, to detect the flood features for disambiguating the dot features.
    Type: Application
    Filed: October 4, 2019
    Publication date: August 12, 2021
    Applicant: Google LLC
    Inventors: Edward T. Chang, Mykhaylo Kurinnyy, Zhaowei Wang, Jonathan James Taylor
  • Patent number: 11069117
    Abstract: Systems and methods for generating three-dimensional models having regions of various resolutions are provided. In particular, imagery data can be captured and utilized to generate three-dimensional models. Regions of texture can be mapped to regions of a three-dimensional model when rendered. Resolutions of texture can be selectively altered and regions of texture can be selectively segmented to reduce texture memory cost. Texture can be algorithmically generated based on alternative texturing techniques. Models can be rendered having regions at various resolutions.
    Type: Grant
    Filed: May 6, 2019
    Date of Patent: July 20, 2021
    Assignee: Matterport, Inc.
    Inventors: Daniel Ford, Matthew Tschudy Bell, David Alan Gausebeck, Mykhaylo Kurinnyy
  • Patent number: 10984244
    Abstract: 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.
    Type: Grant
    Filed: January 14, 2020
    Date of Patent: April 20, 2021
    Assignee: Matterport, Inc.
    Inventors: Gunnar Hovden, Mykhaylo Kurinnyy
  • Publication number: 20200151454
    Abstract: 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.
    Type: Application
    Filed: January 14, 2020
    Publication date: May 14, 2020
    Inventors: Gunnar Hovden, Mykhaylo Kurinnyy
  • Patent number: 10650106
    Abstract: Systems and methods are provided for automatically separating and reconstructing individual stories of a three-dimensional model of a multi-story structure based on captured image data of the multi-story structure. In an aspect, a system is provided that includes an analysis component configured to analyze a three-dimensional model of structure comprising a plurality of stories generated based on captured three-dimensional image data of the structure and identify respective stories of the plurality of stories to which features of a three-dimensional model are associated. The system further includes a separation component configured to separate the respective stories from one another based on the features respectively associated therewith, and an interface component configured to generate a graphical user interface that facilitates viewing the respective stories as separated from one another.
    Type: Grant
    Filed: January 28, 2016
    Date of Patent: May 12, 2020
    Assignee: Matterport, Inc.
    Inventors: Matthew Tschudy Bell, Haakon Erichsen, Mykhaylo Kurinnyy
  • Patent number: 10534962
    Abstract: 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.
    Type: Grant
    Filed: June 17, 2017
    Date of Patent: January 14, 2020
    Assignee: Matterport, Inc.
    Inventors: Gunnar Hovden, Mykhaylo Kurinnyy, Matthew Bell
  • Publication number: 20190259194
    Abstract: Systems and methods for generating three-dimensional models having regions of various resolutions are provided. In particular, imagery data can be captured and utilized to generate three-dimensional models. Regions of texture can be mapped to regions of a three-dimensional model when rendered. Resolutions of texture can be selectively altered and regions of texture can be selectively segmented to reduce texture memory cost. Texture can be algorithmically generated based on alternative texturing techniques. Models can be rendered having regions at various resolutions.
    Type: Application
    Filed: May 6, 2019
    Publication date: August 22, 2019
    Inventors: Daniel Ford, Matthew Tschudy Bell, David Alan Gausebeck, Mykhaylo Kurinnyy
  • Patent number: 10325399
    Abstract: Systems and methods for generating three-dimensional models having regions of various resolutions are provided. In particular, imagery data can be captured and utilized to generate three-dimensional models. Regions of texture can be mapped to regions of a three-dimensional model when rendered. Resolutions of texture can be selectively altered and regions of texture can be selectively segmented to reduce texture memory cost. Texture can be algorithmically generated based on alternative texturing techniques. Models can be rendered having regions at various resolutions.
    Type: Grant
    Filed: June 22, 2018
    Date of Patent: June 18, 2019
    Assignee: Matterport, Inc.
    Inventors: Daniel Ford, Matthew Tschudy Bell, David Alan Gausebeck, Mykhaylo Kurinnyy
  • Publication number: 20180365496
    Abstract: 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.
    Type: Application
    Filed: June 17, 2017
    Publication date: December 20, 2018
    Inventors: Gunnar Hovden, Mykhaylo Kurinnyy, Matthew Bell
  • Publication number: 20180300936
    Abstract: Systems and methods for generating three-dimensional models having regions of various resolutions are provided. In particular, imagery data can be captured and utilized to generate three-dimensional models. Regions of texture can be mapped to regions of a three-dimensional model when rendered. Resolutions of texture can be selectively altered and regions of texture can be selectively segmented to reduce texture memory cost. Texture can be algorithmically generated based on alternative texturing techniques. Models can be rendered having regions at various resolutions.
    Type: Application
    Filed: June 22, 2018
    Publication date: October 18, 2018
    Inventors: Daniel Ford, Matthew Tschudy Bell, David Alan Gausebeck, Mykhaylo Kurinnyy
  • Patent number: 10055876
    Abstract: Systems and methods for generating three-dimensional models having regions of various resolutions are provided. In particular, imagery data can be captured and utilized to generate three-dimensional models. Regions of texture can be mapped to regions of a three-dimensional model when rendered. Resolutions of texture can be selectively altered and regions of texture can be selectively segmented to reduce texture memory cost. Texture can be algorithmically generated based on alternative texturing techniques. Models can be rendered having regions at various resolutions.
    Type: Grant
    Filed: June 6, 2014
    Date of Patent: August 21, 2018
    Assignee: Matterport, Inc.
    Inventors: Daniel Ford, Matthew Tschudy Bell, David Alan Gausebeck, Mykhaylo Kurinnyy
  • Publication number: 20180144535
    Abstract: Systems and methods for generating three-dimensional models having regions of various resolutions are provided. In particular, imagery data can be captured and utilized to generate three-dimensional models. Regions of texture can be mapped to regions of a three-dimensional model when rendered. Resolutions of texture can be selectively altered and regions of texture can be selectively segmented to reduce texture memory cost. Texture can be algorithmically generated based on alternative texturing techniques. Models can be rendered having regions at various resolutions.
    Type: Application
    Filed: June 6, 2014
    Publication date: May 24, 2018
    Inventors: Daniel Ford, Matthew Tschudy Bell, David Alan Gausebeck, Mykhaylo Kurinnyy
  • Publication number: 20160217225
    Abstract: Systems and methods are provided for automatically separating and reconstructing individual stories of a three-dimensional model of a multi-story structure based on captured image data of the multi-story structure. In an aspect, a system is provided that includes an analysis component configured to analyze a three-dimensional model of structure comprising a plurality of stories generated based on captured three-dimensional image data of the structure and identify respective stories of the plurality of stories to which features of a three-dimensional model are associated. The system further includes a separation component configured to separate the respective stories from one another based on the features respectively associated therewith, and an interface component configured to generate a graphical user interface that facilitates viewing the respective stories as separated from one another.
    Type: Application
    Filed: January 28, 2016
    Publication date: July 28, 2016
    Inventors: Matthew Tschudy Bell, Haakon Erichsen, Mykhaylo Kurinnyy