Object recognition for bottom of basket detection using neural network

An object recognition system for a cart in a checkout lane at a retail store location, the system comprising:

• at least one camera that collects a stream of images from a checkout lane, where each image includes color data and coordinate data;
• a computing device that receives the stream of images from the camera according to a sampling rate, the computing device including
• an application component that applies each image from the stream of images to a convolutional neural network to determine a set of class scores for each image,
• an analyzing component that selects a class score from the set of class scores for an image where the class score is the highest value in the set of class scores, meets a threshold, or is the highest value in the set of class scores and meets the threshold;
• cross-references the selected class score to a BOB classification value from a table of BOB classification labels;
• and sets a BOB status for the checkout lane using the BOB classification value,
• a translation component that translates the BOB status to a BOB indicator, and
• a communication component that communicates the BOB indicator to a checkout lane device, wherein communication of the BOB indicator to a checkout lane device comprises production of the BOB indicator as at least one of light from a light device of the checkout lane device and sound from a speaker device of the checkout lane device.

A computer program product for object recognition for a cart in a checkout lane at a retail store location, the computer program product stored on a non-transitory computer-readable medium and including instructions adapted to cause a computer to execute steps comprising:

• collecting a stream of images from a checkout lane at a sampling rate, where each image includes color data and coordinate data;
• applying each image from the stream of images to a convolutional neural network to determine a set of class scores for each image;
• selecting a class score from the set of class scores for an image where the class score is the highest value in the set of class scores, meets a threshold, or is the highest value in the set of class scores and meets the threshold;
• cross-referencing the selected class score to a BOB classification value from a table of BOB classification labels;
• setting a BOB status for the checkout lane using the BOB classification value;
• translating the BOB status to a BOB indicator;
• and
• communicating the BOB indicator to a checkout lane device, wherein communicating the BOB indicator to a checkout lane device comprises at least one of displaying the BOB indicator on a light device of the checkout lane device and sounding the BOB indicator on a speaker device of the checkout lane device.