Invention Grant
- Patent Title: Depth from time-of-flight using machine learning
-
Application No.: US15672261Application Date: 2017-08-08
-
Publication No.: US10311378B2Publication Date: 2019-06-04
- Inventor: Sebastian Nowozin , Amit Adam , Shai Mazor , Omer Yair
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Main IPC: G06N99/00
- IPC: G06N99/00 ; G06K9/62 ; G06K9/20 ; G06T7/50 ; G01S17/89 ; G06N20/00 ; G01S7/48 ; G06T7/521 ; G01S17/36 ; G01S17/66

Abstract:
A depth detection apparatus is described which has a memory storing raw time-of-flight sensor data received from a time-of-flight sensor. The depth detection apparatus also has a trained machine learning component having been trained using training data pairs. A training data pair comprises at least one simulated raw time-of-flight sensor data value and a corresponding simulated ground truth depth value. The trained machine learning component is configured to compute in a single stage, for an item of the stored raw time-of-flight sensor data, a depth value of a surface depicted by the item, by pushing the item through the trained machine learning component.
Public/Granted literature
- US20180129973A1 DEPTH FROM TIME-OF-FLIGHT USING MACHINE LEARNING Public/Granted day:2018-05-10
Information query