Automated probabilistic axiom generation and incremental updates
US11854252B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 22, 2022 |
| Grant date | Dec 26, 2023 |
| Priority date | — |
| Expiry date | Mar 22, 2042 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N23/61
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
Described is a system for evaluating and correcting perception errors in object detection and recognition. The system receives perception data from an environment proximate a mobile platform. Perception probes are generated from the perception data which describe perception characteristics of object detections in the perception data. For each perception probe, probabilistic distributions for true positive and false positive values are determined, resulting in true positive and false negative perception probes. Statistical characteristics of true positive perception probes and false positive perception probes are then determined. Based on the statistical characteristics, true positive perception probes are clustered. An axiom is generated to determine statistical constraints for perception validity for each perception probe cluster. The axiom is evaluated to classify the perception probes as valid or erroneous. Optimal perception parameters are generated by solving an optimization problem based on the axiom. The perception module is adjusted based on the optimal perception parameters.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.