The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 19, 2025

Filed:

Dec. 13, 2021
Applicant:

Zoox, Inc., Foster City, CA (US);

Inventors:

Bryce A. Evans, San Mateo, CA (US);

Derek Xiang Ma, San Carlos, CA (US);

Sarah Tariq, Palo Alto, CA (US);

Assignee:

Zoox, Inc., Foster City, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/246 (2017.01); G01S 17/58 (2006.01); G01S 17/89 (2020.01); G01S 17/931 (2020.01); G05D 1/00 (2006.01); G06N 3/044 (2023.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01); G06T 7/174 (2017.01); G06V 10/20 (2022.01); G06V 10/26 (2022.01); G06V 10/62 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/58 (2022.01);
U.S. Cl.
CPC ...
G06T 7/246 (2017.01); G01S 17/58 (2013.01); G01S 17/89 (2013.01); G01S 17/931 (2020.01); G05D 1/0088 (2013.01); G06N 3/044 (2023.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06T 7/174 (2017.01); G06V 10/255 (2022.01); G06V 10/26 (2022.01); G06V 10/62 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/58 (2022.01); G06V 20/584 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30236 (2013.01); G06T 2207/30241 (2013.01); G06T 2207/30261 (2013.01);
Abstract

Techniques are disclosed for tracking objects in sensor data, such as multiple images or multiple LIDAR clouds. The techniques may include comparing segmentations of sensor data such as by, for example, determining a similarity of a first segmentation of first sensor data and a second segmentation of second sensor data. Comparing the similarity may comprise determining a first embedding associated with the first segmentation and a second embedding associated with the second segmentation and determining a distance between the first embedding and the second embedding. The techniques may improve the accuracy and/or safety of systems integrating the techniques discussed herein.


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