US 12,223,570 B2
Systems and methods for high dimensional 3D data visualization
Ciro Donalek, Pasadena, CA (US); Michael Amori, Pasadena, CA (US); Justin Gantenberg, Pasadena, CA (US); Sarthak Sahu, Pasadena, CA (US); and Aakash Indurkhya, Pasadena, CA (US)
Assigned to Virtualitics, Inc., Pasadena, CA (US)
Filed by Virtualitics, Inc., Pasadena, CA (US)
Filed on Sep. 26, 2022, as Appl. No. 17/935,514.
Application 17/935,514 is a continuation of application No. 17/129,611, filed on Dec. 21, 2020, granted, now 11,455,759.
Application 17/129,611 is a continuation of application No. 16/844,983, filed on Apr. 9, 2020, granted, now 10,872,446, issued on Dec. 22, 2020.
Application 16/844,983 is a continuation of application No. 16/133,631, filed on Sep. 17, 2018, granted, now 10,621,762, issued on Apr. 14, 2020.
Claims priority of provisional application 62/671,378, filed on May 14, 2018.
Prior Publication US 2023/0013873 A1, Jan. 19, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06T 11/20 (2006.01); G06T 17/20 (2006.01)
CPC G06T 11/206 (2013.01) [G06T 17/20 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A data visualization system, comprising:
at least one processor; and
a memory comprising a data visualization application, where the data visualization application directs the at least one processor to:
obtain data comprising a set of records, where each record has a plurality of data dimensions;
identify a target dimension in the plurality of data dimensions;
generate a set of ranking metrics reflecting the impact of non-target dimensions in the plurality of data dimensions to the target dimension;
calculate a set of correlation coefficients reflecting the degree of statistical correlation between each dimension in the plurality of data dimensions;
generate a set of visualization parameters based on the set of ranking metrics and the set of correlation coefficients;
generate a data structure, where the data structure comprises:
a first list comprising locations of points in a set of unrendered points, where each unrendered point is located in 3D space and represents at least one record from the set of records; and
a second list comprising visualization information describing how to render a set of 3D objects, where each 3D object is centered around a respective unrendered point in the set of unrendered points, based on the visualization parameters; and
render a visualization of the target dimension and at least one non-target dimension using the data structure.