US 11,928,856 B2
Computer vision and speech algorithm design service
Michael Ebstyne, Seattle, WA (US); Pedro Urbina Escos, Seattle, WA (US); Yuri Pekelny, Seattle, WA (US); Jonathan Chi Hang Chan, Seattle, WA (US); Emanuel Shalev, Sammamish, WA (US); Alex Kipman, Bellevue, WA (US); and Mark Flick, Redmond, WA (US)
Assigned to Microsoft Technology Licensing, LLC., Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on May 5, 2022, as Appl. No. 17/737,911.
Application 17/737,911 is a continuation of application No. 16/138,923, filed on Sep. 21, 2018, granted, now 11,354,459.
Application 16/138,923 is a continuation in part of application No. 15/974,665, filed on May 8, 2018, granted, now 11,087,176, issued on Aug. 10, 2021.
Prior Publication US 2022/0261516 A1, Aug. 18, 2022
Int. Cl. G06V 10/774 (2022.01); G06F 11/36 (2006.01); G06F 30/20 (2020.01); G06F 111/18 (2020.01); G10L 15/01 (2013.01); G06F 18/214 (2023.01)
CPC G06V 10/774 (2022.01) [G06F 11/3684 (2013.01); G06F 30/20 (2020.01); G10L 15/01 (2013.01); G06F 18/214 (2023.01); G06F 2111/18 (2020.01)] 20 Claims
OG exemplary drawing
 
1. A method for selecting a hardware configuration in a simulation of one or more hardware configurations for a sensor platform, the sensor platform comprising one or more virtual sensors and having an environment simulation generated for one or more virtual environments, the method comprising:
generating a motion profile simulating motion of the one or more hardware configurations within the one or more virtual environments;
generating synthetic experiment data for the one or more hardware configurations having the simulated motion within the one or more virtual environments, wherein the synthetic experiment data comprises inertial measurement unit (IMU) data;
simulating movement of the one or more hardware configurations with the simulated motion in the one or more virtual environments;
applying an object tracking service to the simulated movement of the one or more hardware configurations with the simulated motion in the one or more virtual environments to determine performance of object tracking by the one or more hardware configurations;
determining disparity data of a simulated hardware configuration compared with a ground truth for the simulated hardware configuration;
determining the disparity data exceeds a variance threshold from the ground truth; and
based on the disparity data exceeding the variance threshold, directing an artificial intelligence (AI) application to run subsequent testing of the object tracking service against a different synthetic scene, motion, or hardware configuration.