US 11,740,321 B2
Visual inertial odometry health fitting
Oleg Naroditsky, San Francisco, CA (US); Kuen-Han Lin, Mountain View, CA (US); and Dimitrios Kottas, Sunnyvale, CA (US)
Assigned to Apple Inc., Cupertino, CA (US)
Filed by Apple Inc., Cupertino, CA (US)
Filed on Mar. 20, 2018, as Appl. No. 15/926,557.
Claims priority of application No. 20170100543 (GR), filed on Nov. 30, 2017.
Prior Publication US 2019/0164040 A1, May 30, 2019
Int. Cl. G01S 5/16 (2006.01); G06T 7/246 (2017.01); G01S 19/47 (2010.01); G06F 18/21 (2023.01); G06F 18/2413 (2023.01); G06N 3/042 (2023.01); G06V 10/764 (2022.01); G01S 19/52 (2010.01)
CPC G01S 5/16 (2013.01) [G01S 19/47 (2013.01); G06F 18/217 (2023.01); G06F 18/24133 (2023.01); G06N 3/042 (2023.01); G06T 7/251 (2017.01); G06V 10/764 (2022.01); G01S 19/52 (2013.01); G06F 2218/12 (2023.01); G06V 2201/03 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A non-transitory program storage device, readable by one or more programmable control devices and comprising instructions stored thereon to cause the one or more programmable control devices to:
receive one or more visual inertial odometry (VIO) feature measurements associated with each image frame of a set of test image frames from a VIO system, wherein the VIO feature measurements each correspond to a measurement of features detected by the VIO system in processing the set of test image frames to determine location information for the VIO system;
generate a plurality of feature models of a neural network classifier model to estimate health values for the VIO system for a particular feature measurement of the one or more VIO feature measurements, wherein each feature model includes at least one feature model parameter;
determine a plurality of feature health values with the feature models based on the one or more VIO feature measurements, wherein each of the plurality of feature health values correspond to an accuracy of a corresponding feature measurement associated with the feature model;
compare the feature health values with ground truth health scores associated with the set of test image frames to determine one or more errors between the feature health values and the ground truth health scores, wherein the ground truth health scores comprise a set of predetermined health scores corresponding to the VIO system and the set of test image frames; and
update the feature model parameters for one or more of the feature models based on the one or more errors.