US 12,260,574 B2
Image-based keypoint generation
Ronghua Zhang, Campbell, CA (US); Derik Schroeter, Fremont, CA (US); Mengxi Wu, Mountain View, CA (US); and Di Zeng, Sunnyvale, CA (US)
Assigned to NVIDIA CORPORATION, Santa Clara, CA (US)
Filed by NVIDIA Corporation, Santa Clara, CA (US)
Filed on Jun. 21, 2022, as Appl. No. 17/808,045.
Application 17/808,045 is a continuation of application No. 16/912,549, filed on Jun. 25, 2020, granted, now 11,367,208.
Claims priority of provisional application 62/866,362, filed on Jun. 25, 2019.
Prior Publication US 2023/0018923 A1, Jan. 19, 2023
Int. Cl. G06T 7/521 (2017.01); G01C 21/32 (2006.01); G01S 17/89 (2020.01); G06T 7/73 (2017.01)
CPC G06T 7/521 (2017.01) [G01C 21/32 (2013.01); G01S 17/89 (2013.01); G06T 7/73 (2017.01)] 18 Claims
OG exemplary drawing
 
1. A method, comprising:
selecting a first keypoint included in a first image, the first keypoint corresponding to a feature of an area represented by the first image, the selecting of the first keypoint being based at least on:
determining that a second image includes a second keypoint that also corresponds to the feature; and
determining that one or more points of a light detection and ranging (LIDAR) scan also correspond to the feature; and
annotating, based at least on the selecting of the first keypoint, map data with keypoint data that corresponds to the first keypoint, the keypoint data describing the feature corresponding to the first keypoint, wherein one or more pose parameters corresponding to a machine are determined based at least on the map data being annotated, based at least on the selecting of the first keypoint, with keypoint data that corresponds to the first keypoint.