Mona Fathollahi

US Patent:

20200364521, Nov 19, 2020

Filed:

May 15, 2019

Appl. No.:

16/412765

Inventors:

- Sunnyvale CA, US
Mona Fathollahi - Sunnyvale CA, US
Ethan Rublee - Mountain View CA, US
Grace Vesom - Woodside CA, US
William Nguyen - Mountain View CA, US

Assignee:

Matterport, Inc. - Sunnyvale CA

International Classification:

G06K 9/66
G06K 9/62
G06K 7/14

Abstract:

Trained networks configured to detect fiducial elements in encodings of images and associated methods are disclosed. One method includes instantiating a trained network with a set of internal weights which encode information regarding a class of fiducial elements, applying an encoding of an image to the trained network where the image includes a fiducial element from the class of fiducial elements, generating an output of the trained network based on the set of internal weights of the network and the encoding of the image, and providing a position for at least one fiducial element in the image based on the output. Methods of training such networks are also disclosed.

US Patent:

20200364873, Nov 19, 2020

Filed:

May 14, 2019

Appl. No.:

16/412079

Inventors:

- Sunnyvale CA, US
Ethan Rublee - Mountain View CA, US
Mona Fathollahi - Sunnyvale CA, US
Michael Tetelman - Los Gatos CA, US
Ian Meeder - Mountain View CA, US
Varsha Vivek - Seattle WA, US
William Nguyen - San Jose CA, US

Assignee:

Matterport, Inc. - Sunnyvale CA

International Classification:

G06T 7/12
G06T 5/20

Abstract:

Methods and systems regarding importance sampling for the modification of a training procedure used to train a segmentation network are disclosed herein. A disclosed method includes segmenting an image using a trainable directed graph to generate a segmentation, displaying the segmentation, receiving a first selection directed to the segmentation, and modifying a training procedure for the trainable directed graph using the first selection. In a more specific method, the training procedure alters a set of trainable values associated with the trainable directed graph based on a delta between the segmentation and a ground truth segmentation, the first selection is spatially indicative with respect to the segmentation, and the delta is calculated based on the first selection.

US Patent:

20200364878, Nov 19, 2020

Filed:

May 14, 2019

Appl. No.:

16/412183

Inventors:

- Sunnyvale CA, US
Prasanna Krishnasamy - Mountain View CA, US
Mona Fathollahi - Sunnyvale CA, US
Michael Tetelman - Los Gatos CA, US

Assignee:

Matterport, Inc. - Sunnyvale CA

International Classification:

G06T 7/194
G06T 7/11
G06T 11/00
G06N 3/08

Abstract:

Systems and methods for frame and scene segmentation are disclosed herein. One method includes associating a first primary element from a first frame with a background tag, associating a second primary element from the first frame with a subject tag, generating a background texture using the first primary element, generating a foreground texture using the second primary element, and combining the background texture and the foreground texture into a synthesized frame. The method also includes training a segmentation network using the background tag, the foreground tag, and the synthesized frame.

US Patent:

20200364895, Nov 19, 2020

Filed:

May 15, 2019

Appl. No.:

16/413102

Inventors:

- Sunnyvale CA, US
Mona Fathollahi - Sunnyvale CA, US
Ethan Rublee - Mountain View CA, US
Grace Vesom - Woodside CA, US
William Nguyen - Mountain View CA, US

Assignee:

Matterport, Inc. - Sunnyvale CA

International Classification:

G06T 7/73
G06N 3/08
G06T 7/593

Abstract:

A trained network for point tracking includes an input layer configured to receive an encoding of an image. The image is of a locale or object on which the network has been trained. The network also includes a set of internal weights which encode information associated with the locale or object, and a tracked point therein or thereon. The network also includes an output layer configured to provide an output based on the image as received at the input layer and the set of internal weights. The output layer includes a point tracking node that tracks the tracked point in the image. The point tracking node can track the point by generating coordinates for the tracked point in an input image of the locale or object. Methods of specifying and training the network using a three-dimensional model of the locale or object are also disclosed.

US Patent:

20200364900, Nov 19, 2020

Filed:

May 15, 2019

Appl. No.:

16/412825

Inventors:

- Sunnyvale CA, US
Mona Fathollahi - Sunnyvale CA, US
Ethan Rublee - Mountain View CA, US
Grace Vesom - Woodside CA, US
William Nguyen - Mountain View CA, US

Assignee:

Matterport, Inc. - Sunnyvale CA

International Classification:

G06T 7/73
H04N 5/262
H04N 5/247

Abstract:

Systems and methods for point marking using virtual fiducial elements are disclosed. An example method includes placing a set of fiducial elements in a locale or on an object and capturing a set of calibration images using an imager. The set of fiducial elements is fully represented in the set of calibration images. The method also includes generating a three-dimensional geometric model of the set of fiducial elements using the set of calibration images. The method also includes capturing a run time image of the locale or object. The run time image does not include a selected fiducial element, from the set of fiducial elements, which was removed from a location in the locale or on the object prior to capturing the run time image. The method concludes with identifying the location relative to the run time image using the run time image and the three-dimensional geometric model.