Methods, systems and media for joint manifold learning based heterogenous sensor data fusion
US11210570B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 23, 2018 |
| Grant date | Dec 28, 2021 |
| Priority date | — |
| Expiry date | Oct 31, 2040 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N23/20
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure provides a method for joint manifold learning based heterogenous sensor data fusion, comprising: obtaining learning heterogeneous sensor data from a plurality sensors to form a joint manifold, wherein the plurality sensors include different types of sensors that detect different characteristics of targeting objects; performing, using a hardware processor, a plurality of manifold learning algorithms to process the joint manifold to obtain raw manifold learning results, wherein a dimension of the manifold learning results is less than a dimension of the joint manifold; processing the raw manifold learning results to obtain intrinsic parameters of the targeting objects; evaluating the multiple manifold learning algorithms based on the raw manifold learning results and the intrinsic parameters to determine one or more optimum manifold learning algorithms; and applying the one or more optimum manifold learning algorithms to fuse heterogeneous sensor data generated by the plurality sensors.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.