Multi-task perception network with applications to scene understanding and advanced driver-assistance system
US11462112B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 11, 2020 |
| Grant date | Oct 4, 2022 |
| Priority date | — |
| Expiry date | Apr 28, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG08G1/166
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method is provided in an Advanced Driver-Assistance System (ADAS). The method extracts, from an input video stream including a plurality of images using a multi-task Convolutional Neural Network (CNN), shared features across different perception tasks. The perception tasks include object detection and other perception tasks. The method concurrently solves, using the multi-task CNN, the different perception tasks in a single pass by concurrently processing corresponding ones of the shared features by respective different branches of the multi-task CNN to provide a plurality of different perception task outputs. Each respective different branch corresponds to a respective one of the different perception tasks. The method forms a parametric representation of a driving scene as at least one top-view map responsive to the plurality of different perception task outputs. The method controls an operation of the vehicle for collision avoidance responsive to the at least one top-view map indicating an impending collision.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.