Invention Grant
- Patent Title: Use of machine-trained network for misalignment-insensitive depth perception
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Application No.: US15870020Application Date: 2018-01-12
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Publication No.: US10742959B1Publication Date: 2020-08-11
- Inventor: Andrew Mihal , Steven Teig
- Applicant: Perceive Corporation
- Applicant Address: US CA San Jose
- Assignee: PERCEIVE CORPORATION
- Current Assignee: PERCEIVE CORPORATION
- Current Assignee Address: US CA San Jose
- Agency: Adeli LLP
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G08G1/16 ; H04N13/239 ; G06N3/04 ; G06K9/00 ; G06T7/593

Abstract:
Some embodiments of the invention provide a novel multi-layer node network to reliably determine depth based on a plurality of input sources (e.g., cameras, microphones, etc.) that may be arranged with deviations from an ideal alignment or placement. Determined depths are used, in some embodiments, to process data captured by the plurality of input sources. Other embodiments use the calculated depth to determine whether warnings must be provided or other actions taken. Some embodiments train the multi-layer network using a set of inputs generated with random misalignments incorporated into the training set.
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