Systems and methods of product recognition through multi-model image processing

A system to recognize retail products, comprising:

• an imaging system configured to capture a series of images;
• at least one tangible memory storing a local product database comprising sets of product imaging data, wherein each set of product imaging data corresponds to one of multiple different retail products;
• and
• a decision control circuit communicatively coupled with the memory and configured to:
• process each image of a set of images, captured by the imaging system at different orientations relative to an item within each image of the set of images, by at least a first modeling technique relative to a first image attribute and obtain a corresponding first product identification probability that the item, captured within each of the set of images, is estimated to be a first product;
• process each image of the set of images by a second modeling technique relative to a second image attribute that is different than the first image attribute, and obtain a corresponding second product identification probability that the item, captured within each of the set of images, is estimated to be the first product, and providing first product identification probabilities each corresponding to one of the images of the set of images, and second product identification probabilities each corresponding to one of the images of the set of images;
• collectively evaluate the first product identification probabilities and the second product identification probabilities;
• and
• identify the item as the first product in response to identifying a predefined relationship with a collective threshold probability based on the collective evaluation of the first product identification probabilities and the second product identification probabilities has a predefined relationship with a collective threshold probability.