Geometric confidence for tracking objects
US12136229B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | May 31, 2022 |
| Grant date | Nov 5, 2024 |
| Priority date | — |
| Expiry date | May 4, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/07
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques for training a model for detecting objects in an environment are discussed herein. For example, techniques can include determining losses associated with spatial features of candidate bounding boxes output by a machine-learned (ML) model and utilizing the losses to train the ML model. Techniques may include determining candidate bounding box(es) associated with an object detected in an environment using the ML model and receiving a ground truth bounding box associated with the detected object. A yaw error loss may be determined by comparing yaw features of the candidate bounding box to the ground truth bounding box. The candidate bounding box may be axis aligned with respect to the ground truth bounding box and an intersection over union (IoU) loss may be determined based on an IoU between the axis aligned candidate bounding box and the ground truth bounding box. The ML model may be trained based on the losses.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.