US 12,080,025 B2
Camera-only-localization in sparse 3D mapped environments
Hrushikesh Tukaram Garud, Parbhani (IN); Deepak Poddar, Bengaluru (IN); and Soyeb Noormohammed Nagori, Bengaluru (IN)
Assigned to Texas Instruments Incorporated, Dallas, TX (US)
Filed by TEXAS INSTRUMENTS INCORPORATED, Dallas, TX (US)
Filed on Aug. 15, 2022, as Appl. No. 17/887,580.
Application 17/887,580 is a continuation of application No. 16/854,590, filed on Apr. 21, 2020, granted, now 11,417,017.
Prior Publication US 2022/0392108 A1, Dec. 8, 2022
Int. Cl. G06T 7/00 (2017.01); G01C 21/30 (2006.01); G06T 7/73 (2017.01); G06V 10/98 (2022.01); G06V 20/56 (2022.01); G06V 20/64 (2022.01)
CPC G06T 7/73 (2017.01) [G01C 21/30 (2013.01); G06T 7/75 (2017.01); G06V 10/993 (2022.01); G06V 20/56 (2022.01); G06V 20/647 (2022.01); B60R 2300/302 (2013.01); G06T 2207/30252 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A method comprising:
accessing sensor data associated with an object;
determining, based on the sensor data, a set of feature points;
determining an approximate location for the object;
determining, based on the approximate location and a map header, a subset of a map, wherein the subset of the map specifies a set of map feature points within a volume of area, and wherein the map header specifies, for each map feature point of the set of map feature points, a number of feature descriptors in a set of feature descriptors; and
comparing the set of feature points to the set of map feature points to determine a pose of the object.