MODELING POINT CLOUD DATA USING HIERARCHIES OF GAUSSIAN MIXTURE MODELS

Patent №

US 10,482,196

Granted

2019-11-19

Filed 2016

Owner

NVIDIA CORPORATION

AI components

5

ml · vision · planning · evo · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

15055440

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.

Machine learningVisionPlanningEvolutionary computationAI hardwareG06F 17/18G06F 18/231G06F 18/2415G06F 18/24323G06F 30/20G06N 5/01G06N 7/01G06V 10/7625+3 more

AI classification

Machine learning1.00
Evolutionary computation1.00
AI hardware0.99
Vision0.96
Planning0.93
Knowledge representation0.17
Natural language0.00
Speech0.00

Ownership

NVIDIA CORPORATION

assignment · 378440341

Assignors

ECKART, BENJAMIN DAVID, KIM, KIHWAN, TROCCOLI, ALEJANDRO JOSE, KAUTZ, JAN

On an employer assignment, the assignors are typically the inventors.

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