Willow Garage, LLC

Gm Global Technolgoy Operations, Inc.

Other

Counsyl, Inc.

Stuart Glaser

Wim Meeussen

Eitan Marder-Eppstein

Kyle Allen Lapham

James Cregg

Daniel Delubac

Elliot Branson

Gautier Minster

Juan Fasola

Kyle Vogt

Peter Ming Gao

Matthias Wisniowski

One embodiment is directed to a method for presenting views of a very large point data set, comprising: storing data on a storage system that is representative of a point cloud comprising a very large number of associated points; automatically and deterministically organizing the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; receiving a command from a user of a user interface to present an image based at least in part upon a selected viewing perspective origin and vector; and assembling the image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy.

Point cloud data hierarchy

A system comprises a storage system comprising data representing a point cloud comprising a very large number of associated points; a controller operatively coupled to the storage cluster and configured to organize the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; and a user interface through which a user may select a viewing perspective origin and vector, which may be utilized to command the controller to assemble an image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy, the plurality of data sectors being assembled such that sectors representative of points closer to the selected viewing origin have a higher octree mesh resolution than that of sectors representative of points farther away from the selected viewing origin.

One embodiment is directed to a system for presenting views of a very large point data set, comprising: a storage system comprising data representing a point cloud comprising a very large number of associated points; a controller operatively coupled to the storage cluster and configured to automatically and deterministically organize the point data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; and a user interface through which a user may select a viewing perspective origin and vector, which may be utilized to command the controller to assemble an image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy.

One method embodiment comprises storing data on a storage system that is representative of a point cloud comprising a very large number of associated points; organizing the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; receiving a command from a user of a user interface to present an image based at least in part upon a selected viewing perspective origin and vector; and assembling the image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy, the plurality of data sectors being assembled such that sectors representative of points closer to the selected viewing origin have a higher octree mesh resolution than that of sectors representative of points farther away from the selected viewing origin.

Disclosed herein are high-throughput sample processing systems and waste management systems, and methods of using the same.

High-throughput sample processing systems and methods of use

Systems and methods are provided for analyzing traffic signal lights in order to control an autonomous vehicle. A method includes receiving an image from a camera regarding at least one traffic signal light and receiving data related to the traffic signal light. Neural networks determine location and characteristics of the traffic signal light.

Systems and methods for traffic signal light detection

Methods and systems are provided for tracking an object. The system includes a data receiving module receiving two dimensional imaging data including an object and height map data correlating ground height and location. A two dimensions to three dimensions transformation module determines a location of the object in three dimensional space based on the two dimensional imaging data and the height map data. A tracking module tracks the object using the location of the object.

Growing community of inventors

San Francisco, CA, United States of America

Stuart Glaser