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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.

Patent No.:

US 12681136 B1

PDFFull Text
Date of Patent:
Jul. 14, 2026

Filed:

Oct. 03, 2024

Lidar systems and methods for detection and classification of objects

Applicant:

Innoviz Technologies Ltd., Rosh Ha'Ayin, IL;

Inventors:

Amir Day, Beer Yakov, IL;

Guy Zohar, Netanya, IL;

Julian Vlaiko, Kfar Saba, IL;

Nir Osiroff, Givatayim, IL;

Ovadya Menadeva, Modiin, IL;

Assignee:

Innoviz Technologies Ltd., Rosh Ha'Ayin, IL;

Attorneys:

Meitar Patents LTD.

Daniel Kligler

Primary Examiner:

On S Mung

Int. Cl.
CPC ...
G01S 7/02 (2006.01); A01C 5/04 (2006.01); G01S 7/48 (2006.01); G01S 7/481 (2006.01); G01S 17/04 (2020.01); G01S 17/58 (2006.01); G01S 17/89 (2020.01); G01S 17/894 (2020.01); G01S 17/931 (2020.01); G06F 18/24 (2023.01); G06F 18/25 (2023.01); G06T 7/70 (2017.01); G06V 10/141 (2022.01); G06V 10/60 (2022.01); G06V 10/75 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/58 (2022.01); G06V 20/62 (2022.01);
U.S. Cl.
CPC ...
G01S 7/026 (2013.01); A01C 5/04 (2013.01); G01S 7/4808 (2013.01); G01S 7/4817 (2013.01); G01S 17/04 (2020.01); G01S 17/58 (2013.01); G01S 17/89 (2013.01); G01S 17/894 (2020.01); G01S 17/931 (2020.01); G06F 18/24 (2023.01); G06F 18/256 (2023.01); G06T 7/70 (2017.01); G06V 10/141 (2022.01); G06V 10/60 (2022.01); G06V 10/751 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/58 (2022.01); G06V 20/588 (2022.01); B60W 2420/403 (2013.01); G06T 2207/30256 (2013.01); G06V 20/625 (2022.01);
Abstract

A method for classifying objects in a vehicle's surroundings includes receiving, on a pixel-by-pixel basis, a plurality of measurements associated with LIDAR detection results for a plurality of pixels of a field of view (FOV) of a LIDAR system configured to detect objects in at least part of the vehicle's surroundings, the measurements including at least one of: a presence indication, a surface angle, object surface physical composition, and a reflectivity level, receiving, on the pixel-by-pixel basis, at least one confidence level associated with each received measurement of the plurality of measurements, accessing at least one memory configured to store classification information for classifying a plurality of objects, and associating a plurality of pixels with a particular object based on the classification information and the received measurements with the at least one associated confidence level.

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