US 12,340,521 B2
Training multi-object tracking models using simulation
Ishani Chakraborty, Seattle, WA (US); Jonathan C. Hanzelka, Kenmore, WA (US); Lu Yuan, Redmond, WA (US); Pedro Urbina Escos, Seattle, WA (US); and Thomas M. Soemo, Redmond, WA (US)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on Nov. 13, 2023, as Appl. No. 18/508,224.
Application 18/508,224 is a continuation of application No. 17/585,053, filed on Jan. 26, 2022, granted, now 11,854,211.
Application 17/585,053 is a continuation of application No. 17/026,084, filed on Sep. 18, 2020, granted, now 11,335,008, issued on May 17, 2022.
Prior Publication US 2024/0078682 A1, Mar. 7, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06T 7/20 (2017.01); G06N 20/00 (2019.01); G06T 17/00 (2006.01); G06T 19/20 (2011.01)
CPC G06T 7/20 (2013.01) [G06N 20/00 (2019.01); G06T 17/00 (2013.01); G06T 19/20 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30196 (2013.01); G06T 2207/30241 (2013.01); G06T 2219/2004 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for multi-object tracking, the system comprising:
a processor; and
a computer-readable medium storing instructions that are operative upon execution by the processor to:
locate, within original simulated data for a training image of a plurality of training images, tag data for an object, based at least on an anomaly alert associated with the object in the training image; and
based at least on locating the tag data for the object, modify at least a portion of the tag data for the object from the original simulated data for the training image, thereby generating preprocessed training data from the original simulated data.