Modeling point cloud data using hierarchies of Gaussian mixture models
US10482196B2 · kind B2 · utility
4Cited by
2References
20Claims
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Key dates
| Filing date | Feb 26, 2016 |
| Grant date | Nov 19, 2019 |
| Priority date | — |
| Expiry date | Jan 25, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2111/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method, computer readable medium, and system are disclosed for generating a Gaussian mixture model hierarchy. The method includes the steps of receiving point cloud data defining a plurality of points; defining a Gaussian Mixture Model (GMM) hierarchy that includes a number of mixels, each mixel encoding parameters for a probabilistic occupancy map; and adjusting the parameters for one or more probabilistic occupancy maps based on the point cloud data utilizing a number of iterations of an Expectation-Maximum (EM) algorithm.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.