US 12,322,129 B2
Camera localization
Sudipta Narayan Sinha, Kirkland, WA (US); Ondrej Miksik, Zurich (CH); Joseph Michael Degol, Seattle, WA (US); and Tien Do, Minneapolis, MN (US)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on Feb. 3, 2022, as Appl. No. 17/592,500.
Claims priority of provisional application 63/279,614, filed on Nov. 15, 2021.
Prior Publication US 2023/0154032 A1, May 18, 2023
Int. Cl. G06T 7/70 (2017.01); G06V 10/774 (2022.01); G06V 10/778 (2022.01); G06V 20/64 (2022.01)
CPC G06T 7/70 (2017.01) [G06V 10/7747 (2022.01); G06V 10/7784 (2022.01); G06V 20/64 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for camera localization within a scene, the method comprising:
receiving, at a processor, an image of a scene, the image captured by the camera;
inputting the image to a machine learning model which has been trained for the scene to detect a plurality of 3D scene landmarks, wherein the 3D scene landmarks are specified in a map of the scene, and receiving as output from the machine learning model a plurality of predictions, each prediction comprising a predicted 3D bearing vector originating at the camera and pointing towards a predicted 3D location of one of the 3D scene landmarks; and
using the predictions, computing an estimate of a position and orientation of the camera in the map of the scene.