Computer vision, user segment, and missing item determination

A computing device comprising:

• a digital camera configured to capture a live feed of digital images of a physical environment;
• a display device;
• a processing system;
• and
• a computer-readable storage medium storing instructions that, responsive to execution by the processing system, cause the processing system to perform operations comprising:
• training a machine-learning model with a plurality of digital images that include digital images of similar physical environments to the physical environment, the live feed of digital images captured subsequent to training the machine-learning model;
• identifying at least one item in the physical environment, the at least one item identified from the live feed of digital images using an object recognition technique;
• associating, with the live feed of digital images, information indicative of identified items in the physical environment based on the identifying;
• comparing the information indicative of the identified items to common items from the digital images of similar physical environments based on the trained machine-learning model;
• determining which of the identified items in the physical environment correspond to common items based on the trained machine-learning model;
• determining that at least one common item in the digital images of similar physical environments is missing from the physical environment based on the comparing and the identified items that correspond to common items;
• locating a listing that corresponds to a missing item in the physical environment;
• and
• displaying the listing that corresponds to the missing item as augmented reality on the live feed.

A computer-implemented method comprising:

• training, by at least one computing device, a machine-learning model using a plurality of digital images depicting physical environments and items disposed in the physical environments;
• receiving, by the at least one computing device, an additional digital image subsequent to training the machine-learning model, the additional digital image being included in a live feed of digital images capturing a physical environment;
• determining, by the at least one computing device, that at least one common item in the digital images of similar physical environments to the physical environment is missing from the physical environment based on the additional digital image and the trained machine-learning model;
• locating, by the at least one computing device, augmented reality digital content that corresponds to a missing item in the physical environment;
• and
• outputting, by the at least one computing device, the located augmented reality digital content as part of the live feed of digital images.