US 12,266,148 B2
Real-time detection of lanes and boundaries by autonomous vehicles
Yifang Xu, San Jose, CA (US); Xin Liu, Pleasanton, CA (US); Chia-Chih Chen, San Jose, CA (US); Carolina Parada, Boulder, CO (US); Davide Onofrio, San Francisco, CA (US); Minwoo Park, Cupertino, CA (US); Mehdi Sajjadi Mohammadabadi, Santa Clara, CA (US); Vijay Chintalapudi, Sunnyvale, CA (US); Ozan Tonkal, Munich (DE); John Zedlewski, San Francisco, CA (US); Pekka Janis, Uusimaa (FI); Jan Nikolaus Fritsch, Santa Clara, CA (US); Gordon Grigor, San Francisco, CA (US); Zuoguan Wang, Los Gatos, CA (US); I-Kuei Chen, Milpitas, CA (US); and Miguel Sainz, Palo Alto, CA (US)
Assigned to NVIDIA Corporation, Santa Clara, CA (US)
Filed by NVIDIA Corporation, Santa Clara, CA (US)
Filed on May 1, 2023, as Appl. No. 18/309,882.
Application 18/309,882 is a continuation of application No. 17/222,680, filed on Apr. 5, 2021, granted, now 11,676,364.
Application 17/222,680 is a continuation of application No. 16/286,329, filed on Feb. 26, 2019, granted, now 10,997,433, issued on May 4, 2021.
Claims priority of provisional application 62/636,142, filed on Feb. 27, 2018.
Prior Publication US 2023/0267701 A1, Aug. 24, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06V 10/44 (2022.01); G05D 1/00 (2024.01); G06F 18/2413 (2023.01); G06N 3/084 (2023.01); G06T 7/10 (2017.01); G06V 10/46 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/40 (2022.01); G06V 20/56 (2022.01)
CPC G06V 10/44 (2022.01) [G05D 1/0088 (2013.01); G05D 1/0221 (2013.01); G06F 18/24143 (2023.01); G06N 3/084 (2013.01); G06T 7/10 (2017.01); G06V 10/457 (2022.01); G06V 10/46 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/41 (2022.01); G06V 20/588 (2022.01); G06V 10/471 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
determining, using one or more neural networks and based at least on sensor data obtained using one or more sensors of an ego-machine, one or more edges corresponding to one or more surface marking types;
assigning, based at least on one or more relative locations of the one or more edges with respect to the ego-machine, one or more labels to the one or more edges; and
performing, based at least on the one or more edges and the one or more labels, one or more operations by the ego-machine.