Realtime inventory tracking using deep learning

A method of tracking inventory events, such as puts and takes, in an area of real space, the method including:

• using a plurality of sequences of images of corresponding fields of view in the real space, including inventory display structures, the field of view of each sequence of images overlapping with the field of view of at least one other sequence of images in the plurality of sequences of images;
• identifying locations of inventory display locations in the area of real space in a log data structure including item identifiers and their respective quantities for items identified on inventory display locations;
• finding a location of an inventory event using at least two sequences of images in the plurality of sequences of images;
• identifying an item associated with the inventory event;
• attributing the inventory event to a customer;
• matching location of the inventory event with an inventory location using a procedure including calculating a distance from the location of the inventory event to inventory locations on inventory display structures and matching the inventory event with an inventory location based on the calculated distance;
• and
• detecting departure of the customer from the area of real space using the sequences of images produced by the plurality of cameras and in response updating a store inventory for items associated with inventory events attributed to the customer.

A non-transitory computer readable storage medium impressed with computer program instructions to track inventory events, such as puts and takes, in an area of real space, the instructions, when executed on a processor, implement a method comprising:

• using a plurality of sequences of images of corresponding fields of view in the real space, including inventory display structures, the field of view of each sequence of images overlapping with the field of view of at least one other sequence of images in the plurality of sequences of images;
• identifying locations of inventory display locations in the area of real space in a log data structure including item identifiers and their respective quantities for items identified on inventory display locations;
• finding a location of an inventory event using at least two sequences of images in the plurality of sequences of images;
• identifying an item associated with the inventory event;
• attributing the inventory event to a customer;
• matching location of the inventory event with an inventory location using a procedure including calculating a distance from the location of the inventory event to inventory locations on inventory display structures and matching the inventory event with an inventory location based on the calculated distance;
• and
• detecting departure of the customer from the area of real space using the sequences of images and in response updating a store inventory for items associated with inventory events attributed to the customer.