US 12,444,106 B2
Automated evaluation of spatial relationships in images
Hamid Palangi, Kirkland, WA (US); Besmira Nushi, Woodinville, WA (US); Vibhav Vineet, Bellevue, WA (US); Eric J. Horvitz, Kirkland, WA (US); Semiha E. Kamar Eden, Redmond, WA (US); and Tejas Gokhale, Tempe, AZ (US)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on May 17, 2023, as Appl. No. 18/198,593.
Claims priority of provisional application 63/433,270, filed on Dec. 16, 2022.
Prior Publication US 2024/0203005 A1, Jun. 20, 2024
Int. Cl. G06T 11/60 (2006.01); G06F 40/40 (2020.01); G06T 7/11 (2017.01); G06T 7/60 (2017.01); G06T 7/73 (2017.01)
CPC G06T 11/60 (2013.01) [G06F 40/40 (2020.01); G06T 7/11 (2017.01); G06T 7/60 (2013.01); G06T 7/75 (2017.01); G06T 2207/20081 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
accessing a corpus of images and associated text expressing first spatial relationships between objects in the images;
using a machine-trained objection detection module:
detecting the objects in respective images of the corpus; and
determining respective locations of the detected objects in the respective images;
based at least on the respective locations of the detected objects, determining second spatial relationships between the detected objects in the respective images; and
cleansing the corpus by:
removing individual images from the corpus having first spatial relationships expressed by the text that do not match corresponding second spatial relationships determined from the respective locations of the detected objects; and
retaining, in the corpus, other images having first spatial relationships expressed by the text that match corresponding second spatial relationships determined from the respective locations of the detected objects.