US 12,482,118 B2
Landmark perception for localization in autonomous systems and applications
Joshua Edward Abbott, Draper, UT (US); Amir Akbarzadeh, San Jose, CA (US); Joachim Pehserl, Lynnwood, WA (US); Samuel Ogden, Duvall, WA (US); David Wehr, Redmond, WA (US); and Ke Chen, Cupertino, CA (US)
Assigned to NVIDIA Corporation, Santa Clara, CA (US)
Filed by NVIDIA Corporation, Santa Clara, CA (US)
Filed on Feb. 17, 2023, as Appl. No. 18/171,016.
Prior Publication US 2024/0281988 A1, Aug. 22, 2024
Int. Cl. G06T 7/50 (2017.01); G01S 17/89 (2020.01)
CPC G06T 7/50 (2017.01) [G01S 17/89 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30256 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
clustering a representation of classification data into groups of connected pixels of a common class, the classification data representing one or more classifications of sensor data generated using one or more sensors of an ego-machine;
generating one or more fitted shapes of one or more detected landmarks represented by the classification data based at least on performing one or more iterations of:
fitting one or more candidate fitted shapes to the groups of connected pixels of the common class; and
combining the groups of connected pixels of the common class based at least on the one or more candidate fitted shapes; and
executing one or more navigation or localization operations of the ego-machine based at least on the one or more fitted shapes of the one or more detected landmarks.