Systems and methods for real-time adjustment of neural networks for autonomous tracking and localization of moving subject
US11216954B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 20, 2019 |
| Grant date | Jan 4, 2022 |
| Priority date | — |
| Expiry date | Nov 26, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/07
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A goal of the disclosure is to provide real-time adjustment of a deep learning-based tracking system to track a moving individual without using a labeled set of training data. Disclosed are systems and methods for tracking a moving individual with an autonomous drone. Initialization video data of the specific individual is obtained. Based on the initialization video data, real-time training of an input neural network is performed to generate a detection neural network that uniquely corresponds to the specific individual. Real-time video monitoring data of the specific individual and the surrounding environment is captured. Using the detection neural network, target detection is performed on the real-time video monitoring data and a detection output corresponding to a location of the specific individual within a given frame of the real-time video monitoring data is generated. Based on the detection output, first tracking commands are generated to maneuver and center the camera on the location of the specific individual.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.