US 12,488,587 B2
System and method for capturing images for training of an item identification model
Sumedh Vilas Datar, Grapevine, TX (US); Tejas Pradip Rode, Coppell, TX (US); Sailesh Bharathwaaj Krishnamurthy, Irving, TX (US); and Crystal Maung, Dallas, TX (US)
Assigned to 7-ELEVEN, INC., Irving, TX (US)
Filed by 7-Eleven, Inc., Irving, TX (US)
Filed on Jul. 5, 2024, as Appl. No. 18/764,517.
Application 18/764,517 is a continuation of application No. 18/361,692, filed on Jul. 28, 2023, granted, now 12,073,623.
Application 18/361,692 is a continuation of application No. 17/455,894, filed on Nov. 19, 2021, granted, now 11,790,651, issued on Oct. 17, 2023.
Application 17/455,894 is a continuation in part of application No. 17/362,261, filed on Jun. 29, 2021, granted, now 11,887,332, issued on Jan. 30, 2024.
Prior Publication US 2024/0362912 A1, Oct. 31, 2024
Int. Cl. G06K 9/00 (2022.01); G06F 18/214 (2023.01); G06T 7/55 (2017.01); G06T 11/20 (2006.01); G06V 20/40 (2022.01)
CPC G06V 20/41 (2022.01) [G06F 18/2148 (2023.01); G06T 7/55 (2017.01); G06T 11/20 (2013.01); G06T 2210/12 (2013.01); G06V 20/44 (2022.01)] 9 Claims
OG exemplary drawing
 
1. A system for capturing images for training an item identification model comprising:
a plurality of cameras, wherein each camera is configured to capture images of at least a portion of a platform;
a memory, operable to store an item identification model, wherein the item identification model is configured to identify items based at least in part upon images of the items;
a processor, operably coupled with the memory, and configured to:
obtain an identifier associated with an item;
detect a triggering event at the platform, wherein the triggering event corresponds to a user placing the item on the platform;
cause at least one camera from among the plurality of cameras to capture an image of the item;
extract a set of features associated with the item from the image, wherein each feature corresponds to a physical attribute of the item;
associate the item to the identifier and the set of features; and
add a new entry to a training dataset of the item identification model, wherein the new entry represents the item labeled with at least one of the identifier and the set of features; and
a three-dimensional (3D) sensor positioned above the platform, wherein the 3D sensor is configured to capture overhead depth images of the item placed on the platform, wherein each overhead depth image is configured to capture upward-facing surfaces of the item placed on the platform;
wherein the processor is further configured to:
cause the 3D sensor to capture a depth image of the item;
determine an orientation of the item with respect to the platform;
determine that the orientation of the item is longitudinal with respect to the platform; and
in response to determining that the orientation of the item is longitudinal with respect to the platform, cause a first subset of cameras from among the plurality of cameras to take one or more images of the item, wherein the first subset of cameras are positioned above the platform.