Depth from time-of-flight using machine learning
US9760837B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 13, 2016 |
| Grant date | Sep 12, 2017 |
| Priority date | — |
| Expiry date | Mar 13, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01S17/66
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.