Method for object recognition using queue-based model selection and optical flow in autonomous driving environment, recording medium and device for performing the method
US12223737B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 10, 2021 |
| Grant date | Feb 11, 2025 |
| Priority date | — |
| Expiry date | Nov 19, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An object recognition method using queue-based model selection and optical flow in an autonomous driving environment includes preprocessing data through a dense flow in a matrix form by calculating an optical flow of images captured consecutively in time by a sensor for an autonomous vehicle, generating a confidence mask by generating a vectorized confidence threshold representing a probability that there is a moving object for each cell of the preprocessed matrix, determining whether there is a moving object on the images by mapping the images captured consecutively in time to the confidence mask, and selecting an object recognition model using a tradeoff constant between object recognition accuracy and queue stability in each time unit. Accordingly, it is possible to improve the performance of object recognition in an autonomous driving environment by applying the optical flow to the confidence threshold of the object recognition system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.