Invention Grant
- Patent Title: Fully convolutional interest point detection and description via homographic adaptation
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Application No.: US16190948Application Date: 2018-11-14
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Publication No.: US10977554B2Publication Date: 2021-04-13
- Inventor: Andrew Rabinovich , Daniel DeTone , Tomasz Jan Malisiewicz
- Applicant: Magic Leap, Inc.
- Applicant Address: US FL Plantation
- Assignee: Magic Leap, Inc.
- Current Assignee: Magic Leap, Inc.
- Current Assignee Address: US FL Plantation
- Agency: Kilpatrick Townsend & Stockton LLP
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06N3/08 ; G06N3/04 ; G06T7/00 ; G06K9/46 ; G06K9/62

Abstract:
Systems, devices, and methods for training a neural network and performing image interest point detection and description using the neural network. The neural network may include an interest point detector subnetwork and a descriptor subnetwork. An optical device may include at least one camera for capturing a first image and a second image. A first set of interest points and a first descriptor may be calculated using the neural network based on the first image, and a second set of interest points and a second descriptor may be calculated using the neural network based on the second image. A homography between the first image and the second image may be determined based on the first and second sets of interest points and the first and second descriptors. The optical device may adjust virtual image light being projected onto an eyepiece based on the homography.
Public/Granted literature
- US20190147341A1 FULLY CONVOLUTIONAL INTEREST POINT DETECTION AND DESCRIPTION VIA HOMOGRAPHIC ADAPTATION Public/Granted day:2019-05-16
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